Welcome to my GitHub profile! I’m a Data Scientist and Machine Learning Enthusiast passionate about Generative AI, NLP, and solving real-world problems through data-driven insights. My background blends engineering precision and innovative problem-solving, transitioning from Mechanical Engineering to the exciting world of AI and Data Science.

• Generative AI & NLP: Crafting intelligent systems for document analysis, sentiment prediction, and real-time information extraction tasks.
• Health Tech AI: Building predictive models and insights in Type I diabetes and genome sequencing.
• Big Data: Developing solutions that leverage cloud platforms, distributed computing, and large-scale data manipulation.

• Advanced Transformers: Exploring cutting-edge applications like Temporal Fusion Transformers for time series analysis.
• Deep Learning Frameworks: Improving proficiency in PyTorch, TensorFlow, and HuggingFace for model fine-tuning and deployment.
• Time Series Forecasting: Predicting trends in financial markets, including gold price forecasting using daily data and 15+ features.

1. Real-Time Stock Sentiment Analysis and Prediction System

   • Built a robust real-time stock sentiment analysis pipeline using GPT-4 fine-tuning and Vader SentimentIntensityAnalyzer.
   • Achieved actionable insights by visualizing trends using Seaborn and creating accurate sentiment predictions.

2. Generative AI-Based Document Retrieval System

   • Designed a system integrating Groq AI and OpenAI embeddings for dynamic document queries using LangChain and FAISS.

3. Image Captioning with CNN and LSTM

   • Developed a hybrid model for captioning images in the Flickr8k dataset, achieving BLEU-1 score of 0.52.

4. Layoff Prediction in the Tech Industry

   • Built regression models to analyze the impact of funding and inflation on layoffs, optimizing with Ridge and Lasso techniques.

5. Health Tech AI with XGBoost

   • Implemented machine learning models for Type I diabetes analysis, focusing on patient data insights and prediction accuracy.

6. Gold Price Prediction with TFT

   • Used Temporal Fusion Transformers on time series data to predict trends focusing on accuracy and feature importance.

• Innovative Generative AI applications that address real-world challenges.
• Projects in healthcare AI, such as genome sequencing analysis or predictive models for chronic diseases.
• Open-source projects involving Big Data, NLP, or cloud-based AI solutions.

When I’m not coding, I’m on the football field! As an ardent football fan and active player, I thrive on teamwork, strategy, and the thrill of the game—both in sports and life.

#Hala_madrid

• LinkedIn: linkedin.com/in/satishkc7
• Portfolio_website: Satish_Portfolio

✨ "Turning complex data into actionable insights and pushing the boundaries of AI one project at a time."