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100-days-of-ml-code

100 Days of ML Coding

accent-classifier

algorithms_in_ipython_notebooks

A repository with IPython notebooks of algorithms implemented in Python.

automobile-eda

Exploratory Data Analysis using Python and find insights using Visualization.

automobile_eda

Automobile EDA - Find insights from given Automobile dataset and also find relationships within data ,features visualize it using python (libraries) and Tableau also apply Machine learning algorithm.

autonomous-farm-robot

UG Project 2019-20.

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-dl4nlp

A curated list of awesome Deep Learning for Natural Language Processing resources

awesome-quantum-machine-learning

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

aws-iot-chat-example

💬 Real-time chat application using AWS IoT platform via MQTT over the WebSocket protocol

aws-iot-device-sdk-js

SDK for connecting to AWS IoT from a device using JavaScript/Node.js

aws-iot-examples

Examples using AWS IoT (Internet of Things)

bi-att-flow

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

bidaf

Bidirectional Attention Flow for Machine Comprehension, Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, Hannaneh Hajishirzi https://arxiv.org/abs/1611.01603

calculator

chat-bot

Chatbot created with flask and openai API

chat-gpt

Train a language model from scratch and entirely based on your WhatsApp group chats.

chatbot

cheatsheets-ai

Essential Cheat Sheets for deep learning and machine learning researchers

churn_analysis_python_machine-learning

The goal of the project is to determine the important reasons of employees churn in a company. The dataset has been taken from Kaggle.com. This dataset has 34 features and a target label 'Attrition' with 1470 instances. This project is using various machine learning models- Naive Bayes, Decision Tree, Random Forest, Knn, SVC, LogisticRegression to predict whether the employee will leave the present company or not in future.

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

computerscience

Free tech resources for faculty, students, and dev advocates for use in computer science courses, workshops, and hackathons.

cortex

Build machine learning APIs

courses

fast.ai Courses

credit-risk-analysis

credit-score-predictive-modeling

credit-worthiness--machine-learning

customer-churn-prediction

Predict which telecom customers might leave using IBM Watson Machine Learning

daanet

DAANet: Dual Ask-Answer Network for Machine Reading Comprehension