257--project-gan

amazing-feature-engineering

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

anthropic_llm

app_track

applied-recommender-systems-python

Source Code for 'Applied Recommender Systems with Python' by Akshay Kulkarni, Adarsha Shivananda, Anoosh Kulkarni, and V Adithya Krishnan

autonomous-obstacle-avoidance

background-generator

banking-application

cmpe-255-group-project-fall21

common

contoso-chat

contrastive-predictive-coding

Keras implementation of Representation Learning with Contrastive Predictive Coding

cricket-stat-data-engineering-project

cs229-2018-autumn

All notes and materials for the CS229: Machine Learning course by Stanford University

cs234-reinforcement-learning-winter-2019

My Solutions of Assignments of CS234: Reinforcement Learning Winter 2019

customer_churn_analysis

Customer churn prediction for telecom dataset

cv_resources

e2e-data-engineering

An end-to-end data engineering pipeline that orchestrates data ingestion, processing, and storage using Apache Airflow, Python, Apache Kafka, Apache Zookeeper, Apache Spark, and Cassandra. All components are containerized with Docker for easy deployment and scalability.

experiment_docs

fastapi-microservices

free-courses-with-certificates

Collection of free courses with certificates

fullstack-nanodegree-vm

geometry-dex

PyTorch Code for "Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning"

go_resources

gym-robotics

A collection of robotics simulation environments for reinforcement learning

helpful-script

job_application_tracking

js_resources

leonasting

leonasting.github.io