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500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code

500 AI Machine learning Deep learning Computer vision NLP Projects with code

absa

Aspect Based Unsupervised Sentiment Analysis of reviews

advanced-data-predictive-analytics

Advanced analytics which is used to make predictions about unknown Test-Cases From Test-Data. Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about Test-Data

advanced-mooc-result-scraper-

Advanced Automated Data-Mining Tool For MOOC Result to Scrap in one click.

agent-x

caffe

Caffe: a fast open framework for deep learning.

code_snippets

coding-interview-university

A complete computer science study plan to become a software engineer.

container-service-getting-started-wt

csharptojavaswing

damg6210_group_8

HIPPA Compliant Database

data-engineering-with-databricks-english

django-user-registration-bs4

Django base template with clean and production ready bootstrap4 UI, with all social authentication flows included

eventstreamgpt

Dataset and modelling infrastructure for modelling "event streams": sequences of continuous time, multivariate events with complex internal dependencies.

fidoop-parallel-mining-g39

FPM - via -spark Mapreduce

fidoop-prallel-mining-mapreduce

fim-django

Django Migrations

guides

Guides for learning + doing better web and app development. Created by Coding for Entrepreneurs.

image-upscaling-cnn

This repository contains a jupyter notebook with the implementation of a simple CNN with the objective of demonstrating how these neural networks can be used for image upscaling

interview

📚 CC++ This repository is a summary of the basic knowledge of recruiting job seekers and beginners in the direction of C/C++ technology, including language, program library, data structure, algorithm, system, network, link loading library, interview experience, recruitment, recommendation, etc.

jarvis

Personal Assistant for Linux and macOS

jaypatel15406

kishan-m-r-s

ll1-parser

LL1 parser written in Python

ml-course-notes-shrey

🎓 Sharing course notes on all topics related to machine learning, NLP, and AI.

numpy

The fundamental package for scientific computing with Python.

python-interview-questions

Python Interview Questions ( v3.10.0 )

railway-management-in-java

CML in java for railway reservation system

rclone

"rsync for cloud storage" - Google Drive, S3, Dropbox, Backblaze B2, One Drive, Swift, Hubic, Wasabi, Google Cloud Storage, Yandex Files

recommendation-systems

Recommendation Systems This is a workshop on using Machine Learning and Deep Learning Techniques to build Recommendation Systesm Theory: ML & DL Formulation, Prediction vs. Ranking, Similiarity, Biased vs. Unbiased Paradigms: Content-based, Collaborative filtering, Knowledge-based, Hybrid and Ensembles Data: Tabular, Images, Text (Sequences) Models: (Deep) Matrix Factorisation, Auto-Encoders, Wide & Deep, Rank-Learning, Sequence Modelling Methods: Explicit vs. implicit feedback, User-Item matrix, Embeddings, Convolution, Recurrent, Domain Signals: location, time, context, social, Process: Setup, Encode & Embed, Design, Train & Select, Serve & Scale, Measure, Test & Improve Tools: python-data-stack: numpy, pandas, scikit-learn, keras, spacy, implicit, lightfm Notes & Slides Basics: Deep Learning AI Conference 2019: WhiteBoard Notes | In-Class Notebooks Notebooks Movies - Movielens 01-Acquire 02-Augment 03-Refine 04-Transform 05-Evaluation 06-Model-Baseline 07-Feature-extractor 08-Model-Matrix-Factorization 09-Model-Matrix-Factorization-with-Bias 10-Model-MF-NNMF 11-Model-Deep-Matrix-Factorization 12-Model-Neural-Collaborative-Filtering 13-Model-Implicit-Matrix-Factorization 14-Features-Image 15-Features-NLP Ecommerce - YooChoose 01-Data-Preparation 02-Models News - Hackernews Product - Groceries Python Libraries Deep Recommender Libraries Tensorrec - Built on Tensorflow Spotlight - Built on PyTorch TFranking - Built on TensorFlow (Learning to Rank) Matrix Factorisation Based Libraries Implicit - Implicit Matrix Factorisation QMF - Implicit Matrix Factorisation Lightfm - For Hybrid Recommedations Surprise - Scikit-learn type api for traditional alogrithms Similarity Search Libraries Annoy - Approximate Nearest Neighbour NMSLib - kNN methods FAISS - Similarity search and clustering Learning Resources Reference Slides Deep Learning in RecSys by Balázs Hidasi Lessons from Industry RecSys by Xavier Amatriain Architecting Recommendation Systems by James Kirk Recommendation Systems Overview by Raimon and Basilico Benchmarks MovieLens Benchmarks for Traditional Setup Microsoft Tutorial on Recommendation System at KDD 2019 Algorithms & Approaches Collaborative Filtering for Implicit Feedback Datasets Bayesian Personalised Ranking for Implicit Data Logistic Matrix Factorisation Neural Network Matrix Factorisation Neural Collaborative Filtering Variational Autoencoders for Collaborative Filtering Evaluations Evaluating Recommendation Systems