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I’m Alex

Data Scientist(Python, ML, DL, Transfomers, GenAI)

• Experienced in machine learning, deep learning, and generative AI, dedicated to driving data-driven solutions and innovations

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About Me

Experienced Data Scientist with a strong background in machine learning, deep learning, and generative AI.

Skilled in developing end-to-end data solutions using Python, TensorFlow, PyTorch, and LLM frameworks like LangChain.
Passionate about solving real-world problems through data-driven insights and intelligent automation.
Proven ability to deliver impactful models across domains like NLP, computer vision, and business analytics.
Always eager to innovate, collaborate, and contribute to meaningful tech advancements.

Skills

Python
Pandas and Seaborn
Machine Learning(Scikit-learn)(Regression & Classiifcation)
SQL (MS SQL , My SQL)
Deep Learning(CNN, OpenCV, Keras, PyTorch)
Deep Learning(RNN,LSTM, NLTK, Keras ,PyTorch)
Gen AI (LangChain,LLM, Agent, Transformers)
Flask, Streamlit ,HTML, CSS

EXPERIENCE

Testimonials

Python Project (5/5)

Alexander demonstrated exceptional Python programming skills while working with us on a critical project. He consistently met all deadlines, delivering high-quality work that exceeded expectations. His ability to manage time effectively without sacrificing quality was particularly impressive, making him a reliable and valuable asset to any team."

Python DL Project(5/5)

he is very confident with his work, and id love to work with Alex again. Very good delivery and responsive

Python Project -ML (4.8/5)

Alex was super fast, delivered the needed very soon even with small revision, very good quality & price. Thank you so much. I would highly recommend him.

Python - Streamlit(5/5)

Alexander Reddy is an absolutely excellent Python developer, Streamlit expert, and data scientist. His technical proficiency across these domains is truly impressive. I've been consistently impressed by his ability to tackle complex challenges with elegant and efficient solutions.

Projects

GenAI (LangChain, LLMs, BERT)

  • GenAI-RAG: A research tool designed for efficient information retrieval. It enables users to input article URLs and search through text, PDFs, and web content seamlessly.

  • GenAI-RAG-SQL: Allows users to ask questions in natural language, which are then converted into SQL queries and executed on a MySQL database to fetch relevant answers.

  • GenAI-Gemini Chat Bot: The Gemini Pro/Flash Chat Bot project assists users by enabling chatbot creation with integrated image and text search capabilities.

  • Generative AI for LLM Model Building: Deployed large language models using LLaMA 3 and Gemma 2 to explore advanced generative AI applications.

Deep Learning Projects (RNN, LSTM, CNN)

  • Email/Movie Review Text Classification: Built models using Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks to accurately interpret and classify textual data.

  • Next Word Prediction: Leveraged RNNs and LSTMs on large text datasets to learn contextual dependencies and generate coherent, contextually relevant predictions.

  • Image Captioning: Developed models that combine CNNs for image feature extraction and LSTMs for sequence generation to produce descriptive captions for images.

  • Face Mask Detector: Created a face mask detection system using Keras, TensorFlow, MobileNet, and OpenCV to identify mask usage from live image input.

  • Wound Image Classifier: Built a multi-class classification model (10 categories) for medical wound images, improving accuracy from 50% to 80% through effective training and validation strategies.

  • Facial Expression Recognition: Implemented a CNN-based model to recognize and classify facial expressions from static images.

Machine Learning Projects (Classification & Regression)

  • Visa Approval Classification: Successfully developed and implemented a machine learning model to accurately classify visa approval statuses, enhancing decision-making efficiency and accuracy.

  • Wine Quality Classification: Built a predictive model to assess wine quality based on physicochemical properties, improving quality control and production processes.

  • Telecom Customer Churn Prediction: Designed a model to identify customers likely to churn, enabling proactive retention strategies and reducing attrition.

  • Employee Promotion Prediction: Created a predictive model to determine the likelihood of employee promotions, supporting HR decision-making and career development planning.

  • BigMart Sales Regression: Developed a regression model to forecast BigMart sales, aiding inventory management and optimizing sales strategies.

  • WiDS Datathon 2024 Challenge: Participated in the WiDS Datathon 2024 by building a model that predicts key metrics and outcomes using diverse datasets, contributing to global data science advancements.

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