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Techionik

@hassansuhail93

verified-v2.svg
4.7
14
5.2
5.2
86%

Go Digital with Innovative IT Solutions!

$40 USD / Hour
・
Flag of
United Kingdom (5:45 PM)
・
Joined on April 2, 2024
$40 USD / Hour
・
Empowering Digital Transformation with TECHIONIK LTD At TECHIONIK, we are committed to driving your business’s success through innovative and customized IT solutions. From cloud migration to cybersecurity, and data analytics to AI-powered automation, we provide all solutions! Our Expertise Includes: ✅ Cloud Computing & Migration: Simplify operations with secure, scalable cloud solutions. ✅ Cybersecurity Services: Protect your business with proactive, multi-layered security strategies. ✅ Artificial Intelligence (AI) & Machine Learning (ML): Harness AI for data-driven insights and intelligent automation. ✅ Data Analytics & Business Intelligence (BI): Transform data into actionable insights for strategic growth. ✅ Software Development (SaaS): Build and deploy applications for enhanced customer engagement. ✅ IT Consulting & Managed Services: Optimise IT performance with expert guidance and support. ✅ Digital Transformation & Automation: Boost efficiency with custom automation solutions. ✅ Web & Mobile App Development: Connect with users through high-quality, responsive apps. ✅ Robotic Process Automation (RPA): Automate repetitive tasks to elevate productivity. ✅ IT Infrastructure & Networking: Build a reliable IT backbone for seamless connectivity. ✅ E-commerce & Digital Payment Solutions: Expand your online business with secure solutions. ✅ ERP & CRM Solutions: Streamline operations and strengthen customer relationships. ✅ DevOps & Agile Development: Accelerate development cycles with agile practices. ✅ Business Process Outsourcing (BPO) & IT Support: Streamline operations with outsourcing. ✅ Staff Augmentation Services: Scale your team with skilled professionals, when and where you need them. ✅ Financial & Accounting Services: Streamline financial operations and ensure compliance with expert accounting solutions. Ready to Transform? Connect with us today to explore how we can accelerate your digital transformation journey and deliver real, measurable results.
Verifications
On time
87%
On budget
99%
Accept rate
100%
Repeat hire rate
10%
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Portfolio

Portfolio

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Web Development (15)
ML/AI (6)
11811414
LLaMA (Large Language Model for Meta AI) represents an innovative approach to leveraging large language models for research purposes and question-answering tasks. By employing LLaMA in a research-based context, scientists and researchers can utilize its vast knowledge base and advanced language understanding capabilities to explore complex scientific topics, analyze datasets, and generate insights.
Large Language Model with Meta AI
LLaMA (Large Language Model for Meta AI) represents an innovative approach to leveraging large language models for research purposes and question-answering tasks. By employing LLaMA in a research-based context, scientists and researchers can utilize its vast knowledge base and advanced language understanding capabilities to explore complex scientific topics, analyze datasets, and generate insights.
Large Language Model with Meta AI
11811412
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
11811409
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
11811407
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
11811405
Creating a chatbot that can answer questions by parsing Wikipedia content using NLTK (Natural Language Toolkit) and Selenium for web scraping involves to parse the Wikipedia Context
Natural Language Processing with Natural Language Tool Kit
Creating a chatbot that can answer questions by parsing Wikipedia content using NLTK (Natural Language Toolkit) and Selenium for web scraping involves to parse the Wikipedia Context
Natural Language Processing with Natural Language Tool Kit
11811403
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
11811414
LLaMA (Large Language Model for Meta AI) represents an innovative approach to leveraging large language models for research purposes and question-answering tasks. By employing LLaMA in a research-based context, scientists and researchers can utilize its vast knowledge base and advanced language understanding capabilities to explore complex scientific topics, analyze datasets, and generate insights.
Large Language Model with Meta AI
LLaMA (Large Language Model for Meta AI) represents an innovative approach to leveraging large language models for research purposes and question-answering tasks. By employing LLaMA in a research-based context, scientists and researchers can utilize its vast knowledge base and advanced language understanding capabilities to explore complex scientific topics, analyze datasets, and generate insights.
Large Language Model with Meta AI
11811412
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
Fine-tuning a Large Language Model (LLM) for science exams involves adapting the model's knowledge and capabilities to comprehend and answer questions related to various scientific disciplines. By training the LLM on a dataset consisting of science exam questions along with their corresponding answers or solutions, the model can learn to understand the nuances of scientific concepts and effectively provide accurate responses to exam-style queries.
Large Language Model
11811409
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
BERT (Bidirectional Encoder Representations from Transformers) is a powerful pre-trained language model developed by Google. Fine-tuning a BERT model for sentiment analysis involves leveraging its contextual understanding of language to classify text based on sentiment. By training BERT on a labeled dataset of sentiment-labeled text, the model learns to accurately predict the sentiment (positive, negative, or neutral) of new text inputs. Fine-tuning BERT for sentiment analysis enables it to capture nuanced contextual information and improve the accuracy of sentiment classification tasks.
Bidirectional Encoder Representations from Transformers
11811407
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
Analyzing a football playground using YOLOv8 (You Only Look Once version 8) for object detection and keypoint detection involves several steps. YOLOv8 is a state-of-the-art object detection algorithm known for its speed and accuracy.
Computer Vision and Object Detection
11811405
Creating a chatbot that can answer questions by parsing Wikipedia content using NLTK (Natural Language Toolkit) and Selenium for web scraping involves to parse the Wikipedia Context
Natural Language Processing with Natural Language Tool Kit
Creating a chatbot that can answer questions by parsing Wikipedia content using NLTK (Natural Language Toolkit) and Selenium for web scraping involves to parse the Wikipedia Context
Natural Language Processing with Natural Language Tool Kit
11811403
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
Naive Bayes is a simple but powerful probabilistic classifier based on Bayes' theorem with the "naive" assumption of independence between features. It's commonly used for classification tasks. In the context of predicting Iris species, Naive Bayes can be applied by assuming independence between the features (e.g., sepal length, sepal width, petal length, petal width) given the class labels (Iris species)
Regression With Naive Bayes
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4.7 · 14 Reviews
Reviews
User Avatar
Modern Business Info Wix Site Design • £500 GBP
Easy to work with. Would recommend
Saulius M.
@smwelding
•
Flag of
Letchworth Garden City, United Kingdom
•
26 days ago
Share
S
Google My Business Review Management System with Dashboard on Datastudio • $600 CAD
Awesome support, thanks to haseeb for wonderful work.
Sathishkumar S.
@sathishkumars4
•
Flag of
North York, Canada
•
2 months ago
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AI Transaction Tracker Accuracy Enhancement • $400 USD
It was amazing experience hiring the team and got my project done! Thank you for all your support and dedication, keep it up!
Dawit K.
@burukey
•
Flag of
Addis Ababa, Ethiopia
•
2 months ago
Share
S
Retail Landing page design • $350 CAD
He was awesome, Tech expert , easy to communicate, reliable vendor, Fast delivery, Quick solution provider. I am sure I am coming back to you with load of projects be ready.
Sathishkumar S.
@sathishkumars4
•
Flag of
North York, Canada
•
3 months ago
Share
User Avatar
AI-Driven Restaurant Reservation System MVP • $49 USD
I had a frustrating experience with this freelance team over a three-month period with no progress or deliverables. Communication was poor, with slow or no responses to my requests. Deadlines were repeatedly pushed back without explanation, and I received no updates or tangible results. It felt like they lacked the competence or professionalism to handle the project. I cannot recommend them for development work and advise seeking a team that values communication and reliability.
Ahmet Can A.
@canaksoy
•
Flag of
Ä°STANBUL, Turkey
•
4 months ago
Share
Experience
CEO
Jun, 2023 - Present
•
1 year, 6 months
Techionik Ltd
Jun, 2023 - Present
•
1 year, 6 months
Get professionals for ML, AI solutions and present your business online with Techionik!
Jun, 2023 - Present
•
1 year, 6 months
Education
Birmingham City University
2017 - 2019
•
2 years
Master's of Business Administration
Flag of
United Kingdom
2017 - 2019
•
2 years
Birmingham City University
2014 - 2017
•
3 years
Bachelor's Accounting and Finance
Flag of
United Kingdom
2014 - 2017
•
3 years
Qualifications
Diversity, Inclusion, and Belonging
2020
LinkedIn
Certified in Diversity, Inclusion, and Belonging from LinkedIn, skilled in fostering environments that embrace and celebrate diverse perspectives. Equipped with strategies to cultivate inclusive cultures, promote equity, and foster a sense of belonging for all individuals within organizational settings.
2020
Proven Tips For Managing Your Time
2021
LinkedIn
Certified in Time Management Mastery by LinkedIn, adept in implementing proven strategies to optimize productivity and efficiency. Equipped with techniques to prioritize tasks, streamline workflows, and maximize the use of available time resources for enhanced personal and professional effectiveness.
2021
Learning LinkedIn Sale Navigator
2021
LinkedIn
Certified in LinkedIn Sales Navigator Mastery, proficient in navigating the digital landscape to identify and capitalize on strategic sales opportunities. Skilled in leveraging advanced tools and insights to streamline prospecting efforts and cultivate meaningful client relationships.
2021
Certifications
P
Preferred Freelancer Program SLA
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