Implementing a 2 layered neural network from scratch using numpy. We will use the Bike Share dataset from UCLI repository to solve a regression problem and test out neural network.

ocr_tts_engines

The OCR and TTS engines supporting ttsdaisy_v4 (https://github.com/vikramriyer/ttsdaisy_v4)

This application helps people poll about current things. For ex: if a person is at a certain place and wants to find out the best places nearby for a certain kind of cuisine. He can check options on Zomato and create a poll. Only people who have been to the place and are his connections can upvote or answer the poll.

predict_fraud_using_machine_learning

The Enron email dataset contains approximately 500,000 emails generated by employees of the Enron Corporation. It was obtained by the Federal Energy Regulatory Commission during its investigation of Enron's collapse. Our aim is to predict whether a given person is s person of interest, by using machine learning models.

project-dog-classification

retailer

sentdex_ml

stanford-cs-229-machine-learning

VIP cheatsheets for Stanford's CS 229 Machine Learning

system_design

This repository has content related to the System Design for popular and unpopular applications

teach_a_car_to_drive_using_deep_learning

In this project, we will use a deep neural network to teach itself to drive by watching us drive. This tasks is also referred to as behavioural cloning.

text_learning

titanic_survival_data_analysis

This project analyzes the Titanic data to find interesting results about the reason that helped the survival of the people. We will use python's seaborn library to do the visualizations.