Jayant Verma's Projects
This project uses Natural Language Processing (NLP) to analyze tweets and predict whether they contain cyberbullying content. It categorizes cyberbullying into six categories: Age, Ethnicity, Gender, Religion, Other Cyberbullying.
It includes full exploratory data analysis (EDA) and preprocessing steps before applying machine learning algorithms. The project uses various datasets and covers data wrangling, exploratory data analysis, data visualization, feature engineering
This project is part of the IBM Data Science Professional Certificate course. It aims to identify the best classifier to predict whether the first stage of a Falcon9 rocket will land successfully, helping SpaceX minimize costs.
Config files for my GitHub profile.
A repository documenting my journey into Machine Learning (ML) & Artificial Intelligence (AI). Regular updates, code snippets, projects, resources, and tutorials shared as I explore these captivating fields. Join me as we delve deeper into ML & AI together! š
LlamaIndex (formerly GPT Index) is a data framework for your LLM applications
Chat with your data (SQL, CSV, pandas, polars, noSQL, etc). PandasAI makes data analysis conversational
Agentic Workflow with Quantized Models
This project aims to predict employee salaries based on their experience. It involves data wrangling, exploratory data analysis, data visualization, and applies linear regression for prediction.
This project is a comprehensive tool that combines both fundamental and technical analysis to provide a holistic view of any stock. It is designed to scrape data from websites such as Yahoo Finance and perform detailed analysis on the collected data, delivering valuable insights and information about a particular stock.
This project aims to predict student grades using various independent features. It involves data wrangling, exploratory data analysis, data visualization, and linear regression. The project uses Python and Jupyter notebooks for implementation.
This project uses machine learning to predict the prices of used phones based on various features like brand, operating system, and new price. The model is built using Python and Flask, and deployed as a web app on Azure.
A high-throughput and memory-efficient inference and serving engine for LLMs
Scrape stock price history from new (Spring 2017) Yahoo Finance layout
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent