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ML Soft Tech

@mza5ab8dc9be9a8c

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4,7
98
6,3
6,3
96%

Generative ai | Data Science | Machine Learning

$50 USD / hora
Bandera de
United Kingdom (3:38 a. m.)
Se unió el marzo 26, 2018
$50 USD / hora
Thanks for being here on my profile! ✅ I have 8+ years of experience specific in Data Science. I'm eager to apply my skills to meet your needs, ensuring your satisfaction. My expertise spans Generative ai, Machine Learning and Deep Learning, with a focus on NLP, Computer Vision, and Time Series analysis. Additionally, I actively contribute to projects involving Generative AI, including work with GPT, Falcon, OpenAI and LLM model training on custom knowledge base. Feel free to avail yourself of my services—I'm here to assist you! I have been working on the following projects: ✅ Classification ✅ Regression ✅ Clustering ✅ Dimensionality Reduction ✅ Prediction ✅ Recognition ✅ Time Series Forecasting ✅ Recommender Systems ✅ Sentiment Analysis ✅ NLP(Natural Language Processing) ✅ Big Data Visualisation ✅ Data Mining ✅ Data Analysis ✅ Data warehousing ✅ Data Modelling ✅ So on. . . I can build following models even more: Generative ai: Llam 2, Llama 3, Mpnet, Mixteral, BERTGPT, GPT (2, 3, 4), RoBERTa, DistilBERT, T5, Transformer-XL, Falcon I have built pipelines for text summarization, semantic search, question answer chat bot and text generation using RAG and other state of the art techniques. Deep Learning: Autoencoder, Fewshot learning, Ensemble learning, Stacking models, Transfer Learning, Stacking, GAN, LSTM, CNN, RNN, MLP, ANN, GMM, GRU, RBFN, DBN VGG, Inception, Resent, Xception, YOLO Machine Learning: Random Forest, KNN, SVM, XGBoost, Decision Trees Naive Bayes, Logistic Regression, SGD, AdaBoost, Kmeans Features extraction & selection techniques: PCA, LDA, Information gain, Variance Threshold, L1-based Fasttext, word2vec, TFIDF, BERT SIFT, Texture, GLCM How I do the full project? ✔️ Data Collection ✔️ Data Annotation, Labeling ✔️ Data Augmentation ✔️ Exploratory Data Analysis ✔️ Data Visualization plots ✔️ Data Cleaning ✔️ Data Normalization ✔️ Features Extraction & Selection ✔️ Data Preparation ✔️ Modeling ✔️ Evaluation ✔️ Deployment For coding: Jupyter noyebook, Pycharm, Colab, GCP, AWS, Azure Why you choose me? ✔️ Well commented code ✔️ Free assistance after delivery of work ✔️ Never late ✔️ Quality work ✔️ Plagiarism Free work ✔️ An expert with 7+ year of experience ✅ I would like to work for all kinds of Deep Learning/Machine Learning/Artificial Intelligence/Data Science projects.
Verificaciones
A tiempo
91 %
Dentro del presupuesto
92 %
Aceptar tarifa
89 %
Tasa de recontratación
22 %

Portafolio

Portafolio

9648154
9648152
9233902
9233781
9233763
8894473
9648154
9648152
9233902
9233781
9233763
8894473
Cambios guardados
4.7 · 98 Reviews
Opiniones
Avatar del usuario
Awesome Work thank you and I would glad to continue to work with you
Pavel P.
@freedoom90
Bandera de
Jerusalem, Israel
hace 9 meses
Compartir
K
Working with him is professional and and effective, and the work is very excellent and exceeds expectations very much
Fawaz M.
@kontm2588
Bandera de
hail, Saudi Arabia
hace 2 años
Compartir
Avatar del usuario
struggled with the project brief and failed to deliver. had an illness during the project.
Bhavin P.
@matchstixx
Bandera de
London, United Kingdom
hace 2 años
Compartir
K
The work was perfect and excellent .highly recommend
Fawaz M.
@kontm2588
Bandera de
hail, Saudi Arabia
hace 2 años
Compartir
K
Amazing working with ML Soft Tech , extremely detailed deliverables and super easy to contact i highly recommend again
Fawaz M.
@kontm2588
Bandera de
hail, Saudi Arabia
hace 2 años
Compartir
Experiencia
Machine Learning Engineer
mar, 2015 - Presente
9 años, 10 meses
H2O.ai
mar, 2015 - Presente
9 años, 10 meses
Study and transform data science prototypes Design machine learning systems Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Run machine learning tests and experiments Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary Extend existing ML libraries and frameworks Keep abreast of developments in the field
mar, 2015 - Presente
9 años, 10 meses
Data Analyst
mar, 2010 - mar, 2015
5 años
I&K Data Visualizer
mar, 2010 - mar, 2015
5 años
I'm working on large amounts of data: facts, figures, and number crunching. I see through the data and analyze it to find conclusions. I present data findings and translate the data into an understandable document. I look at the numbers, trends, and data and come to new conclusions based on the findings.
mar, 2010 - mar, 2015
5 años
Educación
University of California, Los Angeles
2009 - 2012
3 años
PhD (Computer Vision and NLP)
Bandera de
United States
2009 - 2012
3 años
Calificaciones
Mathematics for Machine Learning: Multivariate Calculus (2020)
2020
Coursera
We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster.
2020
Neural Networks and Deep Learning
2018
Udemy
I completed the "Neural Networks and Deep Learning" course with the state of art neural networks. I started with the introduction of neural network architectures and then Shallow Neural Network and Deep Neural Networks
2018
Mathematics for Machine Learning: Multivariate Calculus
2020
Coursera
We start at the very beginning with a refresher on the “rise over run” formulation of a slope, before converting this to the formal definition of the gradient of a function. We then start to build up a set of tools for making calculus easier and faster.
2020
Publicaciones
Improving Arabic Multi-Label Emotion Classification using LLM and Hybrid Loss Function
2024
Big Data Research
This study addresses class imbalance and label correlation in multi-label emotion classification for low-resource languages like Arabic. It proposes stacked embeddings from LLMs, meta-learning, and a hybrid loss function combining class weighting, label correlation, and contrastive learning. Using a Bi-LSTM and neural network, the model improves metrics, reduces class disparities, and offers a generalizable framework for low-resource tasks.
2024
A Reliable Approach For Data Security Framework In Cloud Computing Network
2023
Migration Letters
Cloud computing is a key topic in IT, offering network-based computing via the internet. However, data security, including confidentiality, integrity, and trust, remains a critical concern. This research proposes a reliable framework for secure cloud storage by ensuring user authenticity and maintaining data transparency for both providers and users. Trust is evaluated based on availability, reliability, integrity, adaptability, security, response time, and confidentiality.
2023
A robust deep networks based multi-object multi-camera tracking system for city scale traffic
2022
Multimedia Tools and Applications
Vision sensors play a key role in ITS for traffic management, but tracking across non-overlapping cameras is challenging due to vehicle diversity, occlusions, and varying conditions. We propose a deep learning-based MO-MCT framework using Mask R-CNN, NMS, and transfer learning for re-identification. Tested on the AI City Challenge dataset, it achieved an IDF1 score of 0.8289, showcasing robust and accurate vehicle tracking.
2022
Certificaciones
P
Preferred Freelancer Program SLA
Python - Level 2
Python
Python Level 1
Python
Python - Level 3
Python
Basic Numeracy - Level 1
Basic Numeracy
Data Entry
Data Entry
US English - Level 1
US English
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