This repo contains resources on data scince, AI, machine learning, deep learning, data engineering and SQL.
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Natural Language Processing with Python book show how to analyze text with the Natural Language Toolkit.
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Think Stats book covers many of the core statistical concepts for data science including data analysis, distributions, and probability.
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Bayesian Methods for Hackers book bridges the gap between theoretical Bayesian machine learning methods.
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R for Data Science book is one of the best introductions to learning R for data science.
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Machine Learning Yearning book contains practical steps and frameworks for successful machine learning projects by Andrew Ng.
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Hands-on Machine Learning with Scikit-learn and Tensorflow book gives a very good overview of the machine learning process with Scikit-learn and Tensorflow.
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Forecasting: Principles and Practice book offers a very comprehensive overview of methods used for forecasting.
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Deep learning book is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
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Linear Algebra book covers the foundational concepts that would usually be covered in a typical undergraduate course.
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Introduction to Machine Learning with Python book focuses on the practical application of machine learning techniques rather than covering the math behind the field.
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Transformers enable the processing of sequences in a parallel method.
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BERT is an NLP model based on transformers.
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StyleGAN is a generative adversarial network (GAN) introduced by Nvidia researchers in December 2018, and made source available in February 2019.
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CLIP is a neural network trained on a variety of (image, text) pairs.
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The game of Go with deep neural networks paper revealed AlphaGo which defeated the European Go champion by 5 games to 0.
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DNN for YouTube Recommendations paper mentions the architecture of Deep Learning models used for recommendations on YouTube.
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lazypredict helps build a lot of basic models without much code and helps understand which models works better without any parameter tuning.
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PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
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FeatureSelectionGA searches for one of the best feature set from other features in order to attain a high accuracy.
- Kaggle Courses
- Pattern Classification includes tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.
- Feature Selector: Simple Feature Selection in Python
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100 Days Of ML Code repo includes an excellent 100-day plan for learning ML.
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Awesome Machine Learning repo includes a curated list of awesome machine-learning frameworks, libraries, and software (by language).!
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Project-Based Learning repo contains a list of programming tutorials where aspiring software developers learn how to build an application from scratch.
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Homemade Machine Learning repo contains examples of popular machine learning algorithms implemented in Python and explains the math behind them.
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500 AI & Machine-learning Projects with Code repo contains 500 AI, machine learning, deep learning, computer vision, and NLP projects with code.
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Natural Language Processing Tutorial is a tutorial for those who are studying NLP using Pytorch.
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NLP Recipes repo contains examples and best practices for building NLP systems, provided as Jupyter notebooks and utility functions.
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NLP Course course includes lecture and seminar materials about NLP for each week.
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NLP in Python Tutorial covers NLP step-by-step with several Jupyter Notebooks during the tutorial and uses a number of data science libraries along the way.
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Awesome NLP repo contains a curated list of resources dedicated to Natural Language Processing.
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Deep Learning Drizzle is an organized website where you can find all the free courses from Top Universities with their links.
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The Data Engineering Cookbook repo aims to be a starting point for those who want to become data engineers.
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Data Engineering Zoomcamp repo helps you learn data engineering step by step with slides and videos.
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Awesome Data Engineering repo provides a curated list of data engineering tools for software developers
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Udacity Data Engineering Projects repo includes data engineering projects.
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Data Engineering Practice repo helps you develop and learn data engineering skills.
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Awesome Opensource Data Engineering is a this that aims at providing an overview of open-source projects related to data engineering.
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HashtagCashtag shows how to build a big data pipeline for user sentiment analysis on the US stock market.
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Building a Data Engineering Project in 20 Minutes learns web scraping with real-estates, uploading them to S3, Spark, and Delta Lake, and adding Data Science with Jupyter.
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The goal of Web Crawler For Online Inflation project is to calculate inflation rates from first principles.
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This repo contains projects done which applies principles in data engineering.
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Data Engineering Project is an implementation of the data pipeline which consumes the latest news from RSS Feeds and makes them available for users via handy API. The pipeline infrastructure is built using popular, open-source projects.
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This aim of this repository is to help you develop and learn those skills. You can find the high level topics such python data processing, SQL database table design, PySpark, data cleaning.
- An AI Research Assistant: Elicit
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SQLZoo is an interactive, Wiki-based tutorial that provides lessons and projects for beginners in SQL.
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SQLBolt offers easy-to-follow instructions, a simple interface, and interactive exercises to teach basic proficiency in SQL.
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Kaggle provides tutorials to learn SQL for working with databases, using Google BigQuery from introduction to advanced level.
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CodeAcademy teaches you how to communicate with relational databases through SQL.
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Pop SQL allows you to share queries, store commonly used queries in a searchable library, and provides a visual interface for analysis.
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Learning SQL book is for you if you like to learn with a book. This book is available to read for free online via this PDF.
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Khan Academy includes video-based content with detailed explanations
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