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Python
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Mohammad B.

@badriahmadi

monthly-level-three.svg
4,9
10
4,6
4,6
90%

Machine Learning|API|Web Scraping|Multi-Threading

$35 USD / time
・
s flagg
Estonia (3:52 p.m.)
・
Ble med januar 30, 2024
$35 USD / time
・
I am Mohammad Badri Ahmadi, a dedicated freelancer specializing in : ⌨️ Machine Learning Development. ☎️ API Integration. ✂️ Web Scraping & Data Automation. ⚙️ Software Optimization. ⭐️ Data Analysis and Visualization. ✉️ Database Management. With a rich background in Biomedical Engineering and self-taught mastery in Python, Bash, C, alongside robust skills in multi-threading and API utilization, I deliver innovative solutions that propel businesses forward. ✅Expertise That Delivers: [⌨️] Machine Learning Development: Harnessing sophisticated algorithms ⚔️ to build intelligent systems ☕️, enhancing decision-making ⏳, and automating complex processes ⌛️. [☎️] API Mastery: Seamlessly integrating and customizing APIs ✒️ for enhanced functionality and interconnectivity ⚓️ between applications and services. [✂️] Data Engineering: Utilizing powerful web scraping tools ✒️ and techniques for data extraction, coupled with multi-threading ⏳ for efficient data processing and automation ✨. [⚙️] Software Optimization: Maximizing system performance ⚡️ through advanced optimization techniques, ensuring fast ⌚️, reliable ❄️, and efficient software solutions. [⭐️] Data Analysis & Visualization: Turning complex data into actionable insights ❔ with advanced analysis techniques and visually engaging presentations ✨. [✉️] Database Management: Designing, implementing, and managing robust database solutions ☕️ to store, process, and secure vast amounts of data efficiently ⏳. ✅What Sets Me Apart: [✒️] Tailored Solutions: Every project is unique ⭐️, and I pride myself on crafting customized solutions ⛏ that precisely meet your specific challenges and goals. [⚜️] Commitment to Excellence: I am fully committed to delivering superior quality work ✨, on time ⏰ and within budget ⛽️, to not only meet but exceed your expectations. Let's innovate together! Reach out to discuss how we can turn your vision into reality ✈️.
Verifikasjoner
Innen fristen
100 %
Innenfor budsjett
100 %
Akseptrate
100 %
Gjenansettelsesrate
71 %
Freelancer After Effects Designers Estonia
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Portefølje

Portefølje

11719791
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
11719787
With the finesse of a digital archaeologist, my web scraping powers, ignited by multi-threading's fuel, create a potent blast of efficiency and speed. My mastery extends over Python's BeautifulSoup and Scrapy for data extraction, harnessing the concurrency of threading and asyncio to navigate and mine the web's vast expanses swiftly. Bash scripts, enriched with curl commands, complement my toolbox, enabling direct and powerful HTTP interactions. These techniques allow me to automate the capture of celestial wonders from NASA's APOD site and craft trading bots that navigate the financial cosmos with precision. My journey through data's labyrinth is a testament to the power of combining web scraping prowess with multi-threading's might, showcasing a capability to streamline data's journey from source to insight. While these adventures remain largely veiled, I am open to sharing the secrets of my methodologies with fellow explorers upon request.
Web Scraping and Data Automation
With the finesse of a digital archaeologist, my web scraping powers, ignited by multi-threading's fuel, create a potent blast of efficiency and speed. My mastery extends over Python's BeautifulSoup and Scrapy for data extraction, harnessing the concurrency of threading and asyncio to navigate and mine the web's vast expanses swiftly. Bash scripts, enriched with curl commands, complement my toolbox, enabling direct and powerful HTTP interactions. These techniques allow me to automate the capture of celestial wonders from NASA's APOD site and craft trading bots that navigate the financial cosmos with precision. My journey through data's labyrinth is a testament to the power of combining web scraping prowess with multi-threading's might, showcasing a capability to streamline data's journey from source to insight. While these adventures remain largely veiled, I am open to sharing the secrets of my methodologies with fellow explorers upon request.
Web Scraping and Data Automation
11719781
In my work, I excel in integrating diverse APIs across various projects, demonstrating seamless data integration: Indicator-Based Trading Bot: Analyzes market trends via financial APIs, executing trades based on indicators. News-Based Trading Bot: Uses NLP to analyze market sentiment from news with OpenAI's API for trading insights. Automated Data Collection Tools: Scripts for data aggregation, like NASA's APOD API(https://github.com/mhmmdbdrhmd/APOD), showcase web scraping skills. Custom Application Development: Crafts applications with real-time data feeds, integrating dynamic APIs for content updates. These endeavors, though not public, underscore my ability to harness API technology for innovative solutions in trading, data automation, and application development.
API Utilization
In my work, I excel in integrating diverse APIs across various projects, demonstrating seamless data integration: Indicator-Based Trading Bot: Analyzes market trends via financial APIs, executing trades based on indicators. News-Based Trading Bot: Uses NLP to analyze market sentiment from news with OpenAI's API for trading insights. Automated Data Collection Tools: Scripts for data aggregation, like NASA's APOD API(https://github.com/mhmmdbdrhmd/APOD), showcase web scraping skills. Custom Application Development: Crafts applications with real-time data feeds, integrating dynamic APIs for content updates. These endeavors, though not public, underscore my ability to harness API technology for innovative solutions in trading, data automation, and application development.
API Utilization
11719770
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
11719760
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
11719749
In the domain of software optimization and performance tuning, I've honed my skills to achieve peak efficiency and speed across a variety of programming languages, including Bash, C, and Python. My expertise encompasses: Maximizing CPU utilization through advanced multithreading techniques, significantly reducing runtime for computationally intensive tasks. Employing optimization strategies in Bash and C for high-performance computing processes, crucial for projects requiring rapid data processing and analysis. Utilizing Python's multithreading and multiprocessing capabilities to enhance the functionality and responsiveness of applications, showcasing my ability to leverage concurrency for cutting-edge software solutions. This multifaceted approach to software optimization not only demonstrates my technical versatility but also my commitment to pushing the limits of what's possible in software development, ensuring that my projects are not only functional but also efficient and robust
Software Optimization and Performance Tuning
11719791
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
In my ML development, I've harnessed a spectrum of sophisticated methods to advance science and technology. Key techniques include LDA and Pearson correlation for feature selection, enhancing brain-machine interfaces. I've deployed a wide array of classifiers: MLP, kNN, RBF SVM, Gaussian Naive Bayes, Gaussian Process, emphasizing their application in projects like seizure detection and reinforcement learning for brain-machine interfaces, achieving up to 97% accuracy. Neural network models, particularly MLPs with ReLU activation and SGD optimization, played a pivotal role. My work, validated through methods like ten-fold cross-validation, showcases a deep application of ML concepts. Python libraries such as Scikit-Learn, TensorFlow, and Keras underpin these efforts, facilitating complex model development and evaluation.
Machine Learning Development
11719787
With the finesse of a digital archaeologist, my web scraping powers, ignited by multi-threading's fuel, create a potent blast of efficiency and speed. My mastery extends over Python's BeautifulSoup and Scrapy for data extraction, harnessing the concurrency of threading and asyncio to navigate and mine the web's vast expanses swiftly. Bash scripts, enriched with curl commands, complement my toolbox, enabling direct and powerful HTTP interactions. These techniques allow me to automate the capture of celestial wonders from NASA's APOD site and craft trading bots that navigate the financial cosmos with precision. My journey through data's labyrinth is a testament to the power of combining web scraping prowess with multi-threading's might, showcasing a capability to streamline data's journey from source to insight. While these adventures remain largely veiled, I am open to sharing the secrets of my methodologies with fellow explorers upon request.
Web Scraping and Data Automation
With the finesse of a digital archaeologist, my web scraping powers, ignited by multi-threading's fuel, create a potent blast of efficiency and speed. My mastery extends over Python's BeautifulSoup and Scrapy for data extraction, harnessing the concurrency of threading and asyncio to navigate and mine the web's vast expanses swiftly. Bash scripts, enriched with curl commands, complement my toolbox, enabling direct and powerful HTTP interactions. These techniques allow me to automate the capture of celestial wonders from NASA's APOD site and craft trading bots that navigate the financial cosmos with precision. My journey through data's labyrinth is a testament to the power of combining web scraping prowess with multi-threading's might, showcasing a capability to streamline data's journey from source to insight. While these adventures remain largely veiled, I am open to sharing the secrets of my methodologies with fellow explorers upon request.
Web Scraping and Data Automation
11719781
In my work, I excel in integrating diverse APIs across various projects, demonstrating seamless data integration: Indicator-Based Trading Bot: Analyzes market trends via financial APIs, executing trades based on indicators. News-Based Trading Bot: Uses NLP to analyze market sentiment from news with OpenAI's API for trading insights. Automated Data Collection Tools: Scripts for data aggregation, like NASA's APOD API(https://github.com/mhmmdbdrhmd/APOD), showcase web scraping skills. Custom Application Development: Crafts applications with real-time data feeds, integrating dynamic APIs for content updates. These endeavors, though not public, underscore my ability to harness API technology for innovative solutions in trading, data automation, and application development.
API Utilization
In my work, I excel in integrating diverse APIs across various projects, demonstrating seamless data integration: Indicator-Based Trading Bot: Analyzes market trends via financial APIs, executing trades based on indicators. News-Based Trading Bot: Uses NLP to analyze market sentiment from news with OpenAI's API for trading insights. Automated Data Collection Tools: Scripts for data aggregation, like NASA's APOD API(https://github.com/mhmmdbdrhmd/APOD), showcase web scraping skills. Custom Application Development: Crafts applications with real-time data feeds, integrating dynamic APIs for content updates. These endeavors, though not public, underscore my ability to harness API technology for innovative solutions in trading, data automation, and application development.
API Utilization
11719770
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
My work leverages advanced visualization techniques to make complex data analyses accessible and engaging. I've utilized several key Python libraries extensively: Matplotlib & Seaborn: For creating static, animated, and interactive visualizations. Plotly: Enables sophisticated interactive visualizations for deeper data engagement. Pandas Visualization: Offers straightforward plotting capabilities, integrated seamlessly with DataFrames. Bokeh & Dash by Plotly: For interactive plots and web applications, especially useful for real-time data feeds and dynamic displays, such as in my trading bot project. D3.js & NetworkX: Although D3.js is a JavaScript library, I've integrated it within Python environments to leverage its web-based visualization capabilities. NetworkX has been instrumental in visualizing complex networks and graphs.
Data Visualization
11719760
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
My research integrates diverse data analysis techniques across multiple studies, enhancing signal processing and diagnostic accuracy. Methods include high-pass and band-pass filtering for signal integrity, Independent Component Analysis (ICA) for artifact correction, and Fast Fourier Transform (FFT) for detailed signal decomposition. I've applied Pearson correlation for feature optimization, and min/max normalization to ensure real-time applicability. These approaches have been fundamental in advancing brain-machine interfaces, improving seizure detection, and developing high-precision diagnostic models for Alzheimer's disease. Each technique, carefully chosen for its specific application, showcases my adeptness in both individual and integrated signal processing contexts, underlining the depth of my analytical capabilities in biomedical engineering.
Data Analysis
11719749
In the domain of software optimization and performance tuning, I've honed my skills to achieve peak efficiency and speed across a variety of programming languages, including Bash, C, and Python. My expertise encompasses: Maximizing CPU utilization through advanced multithreading techniques, significantly reducing runtime for computationally intensive tasks. Employing optimization strategies in Bash and C for high-performance computing processes, crucial for projects requiring rapid data processing and analysis. Utilizing Python's multithreading and multiprocessing capabilities to enhance the functionality and responsiveness of applications, showcasing my ability to leverage concurrency for cutting-edge software solutions. This multifaceted approach to software optimization not only demonstrates my technical versatility but also my commitment to pushing the limits of what's possible in software development, ensuring that my projects are not only functional but also efficient and robust
Software Optimization and Performance Tuning
Endringer lagret
4.9 · 10 Reviews
Anmeldelser
A
Speed Calculation Using Rexroth Sensor • €700 EUR
Whit Mohammads nowings about Math and his nowings over Machine Learning is he an perfect Guy for complicated Math Projekts.
Andreas D.
@ADemmler
•
s flagg
Munich, Germany
•
3 måneder siden
Del
Brukeravatar
Dynamic NFT Card Design and Animation for Premier Fighting Events • $200 USD
It was a pleasure working with Mohammad, he's a really talented and great artist! Will definitely keep working with him and I totally recommend his services! He always over deliver and made us to be amazed with the quality of his work! Thank you one more time for all your hard and excellent work, Mohammad!
Inteligente Web
@vinivst
•
s flagg
Rio de Janeiro, Brazil
•
8 måneder siden
Del
Brukeravatar
Logo Design for Blockchain Gaming Startup – MetaMatch • $50 USD
He's a true artist that can translate in graphics what you are thinking! Can't thank enough you Mohammad! The results were amazing and would definitely recommend him to anyone who wants a top tier work done on the time!
Inteligente Web
@vinivst
•
s flagg
Rio de Janeiro, Brazil
•
8 måneder siden
Del
Brukeravatar
TikTok Data Automation into Spreadsheet • $200 USD
he was awesome and amazing delivering good quality of code and instructions.
Rishi A.
@avvarurishi123
•
s flagg
TEMPE, United States
•
9 måneder siden
Del
Brukeravatar
Comprehensive Design and Animation for Fantasy Football Game Cards • $150 USD
Great freelancer! Easy to work with and delivering amazing results! Recommended!
Inteligente Web
@vinivst
•
s flagg
Rio de Janeiro, Brazil
•
9 måneder siden
Del
Utdanning
University of Houston
2016 - 2020
•
4 år
PhD in Biomedical Engineering (Dropped Out)
s flagg
United States
2016 - 2020
•
4 år
Sharif University of Technology
2012 - 2016
•
4 år
Bachelor of Engineering in Chemical Engineering
s flagg
Iran, Islamic Republic of
2012 - 2016
•
4 år
Publikasjoner
Real-Time Seizure State Tracking Using Two Channels: A Mixed-Filter Approach
IEEE, 2019 Asilomar Conference
This research develops a real-time, cost-effective seizure tracking system using just two EEG channels. By employing a mixed-filter approach and state-space modeling, it reduces hardware complexity while ensuring high accuracy. Validated on the CHB-MIT database, it achieves excellent accuracy, sensitivity, and a low false positive rate, demonstrating potential for practical monitoring and adaptive therapies.
Near Perfect Neural Critic from Motor Activity for Updating Brain Machine Interfaces
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018
This research outlines the development of an autonomously updating brain-machine interface (BMI) powered by reinforcement learning. A neural critic, derived from motor cortical activity, is key to updating the BMI decoder for enhanced user performance. Demonstrating up to 97% prediction accuracy, this approach marks significant progress in BMI technology, potentially enabling more intuitive and effective prosthetic control for individuals with motor impairments.
An EEG-fNIRS Hybridization Technique in the Four-Class Classification of Alzheimer's Disease
Journal of Neural Engineering, Vol. 18, No. 4, 2021
This paper introduces an innovative EEG-fNIRS hybridization technique for Alzheimer's disease classification into four distinct stages. Leveraging machine learning algorithms, it significantly enhances diagnostic accuracy compared to traditional methods. The approach demonstrates potential for early detection and monitoring of Alzheimer's progression, providing a critical tool for personalized treatment strategies.
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