Useful help link for working with data
Habr, hello. I present to you the main help link for working with data . The material in Google Dock is suitable for both professionals and those who are just learning to work with data. Use and pump skills yourself + share with colleagues.
A further description of the post is the content of the help link. Therefore, you can immediately familiarize yourself with the document. Or start with its contents, which I attach below.
Of course, the entire list of books / services / videos and lectures in the file is incomplete. Therefore, I propose to make this post valuable - add your useful links to comments, the coolest of them I will add to my file.
In this section, I collected books that will help to master mathematics, statistics, data analysis, some programming languages and machine learning.
A complete list of books is here.
This section needs no introduction. It has a list of notebooks and ML and Data Science libraries for various industries. All codes are in Python, and are hosted on GitHub. They will be useful both for expanding horizons and for launching an interesting startup.
A complete list of notebooks by industry is here.
This section contains courses and lectures on data analysis, mathematics, data science and machine learning.
A complete list of courses and lectures is here.
The full list of datasets is here.
A complete list of useful laptops is here.
Having filtered out a large number of sources and subscriptions, I collect for you all the most significant news from the world of machine learning and artificial intelligence. You can read the digest for June here , for the July here. A complete, updated list of news digests is here.
You will learn more information about machine learning and Data Science by subscribing to my account on Habré and the Telegram channel Neuron . Do not skip future articles. In addition, I remind you - add your most useful links to comments, the coolest ones I will add to my file. Share your learning stories, life hacks and knowledge.
All success and knowledge!
A further description of the post is the content of the help link. Therefore, you can immediately familiarize yourself with the document. Or start with its contents, which I attach below.
Of course, the entire list of books / services / videos and lectures in the file is incomplete. Therefore, I propose to make this post valuable - add your useful links to comments, the coolest of them I will add to my file.
Books on ML and DS
In this section, I collected books that will help to master mathematics, statistics, data analysis, some programming languages and machine learning.
- Deep learning in Python . This book is about deep learning by Francois Scholl, who created Keras, the most powerful neural network library.
- Machine Learning and TensorFlow. Beginners in machine learning will appreciate the applied orientation of this book, because its purpose is to introduce the basics, then quickly get down to solving real problems.
- Create a neural network. This book is an introduction to the theory and practice of creating neural networks. It is intended for those who want to know what neural networks are, where they are used and how to create such a network themselves without experience in this field.
A complete list of books is here.
DS and ML Application by Industry
This section needs no introduction. It has a list of notebooks and ML and Data Science libraries for various industries. All codes are in Python, and are hosted on GitHub. They will be useful both for expanding horizons and for launching an interesting startup.
- RobotChef - improving food recipes based on user reviews;
- Food Amenities - forecasting the demand for food products using neural networks;
- Recipe Cuisine and Rating - predicting the name of the cuisine of any dish based on a list of its ingredients;
A complete list of notebooks by industry is here.
Useful courses
This section contains courses and lectures on data analysis, mathematics, data science and machine learning.
- Deep Learning School. Deep Learning School - a circle from the FPMI MIPT, designed for high school students interested in programming and mathematics, as well as students who want to start deep learning. Classes are taught by students of the PhysTech School of Applied Mathematics and Informatics MIPT.
- Introduction to Data Science and Machine Learning. Analysis of central concepts and topics. Acquaintance with such machine learning methods as decision trees and neural networks + the practical part of the course, devoted to acquaintance with the most popular libraries for data analysis - Pandas and Scikit-learn.
- Introduction to neural network theory and deep learning. This course gives an idea of the current state of affairs in the theory of neural networks. Fully connected and convolutional neural networks are considered using examples of classification and search for objects in images.
A complete list of courses and lectures is here.
Dataset Detail
- Game of Thrones Deaths and Battles - This data set combines three data sources, each based on information from a series of books.
- Global Terrorism Database - Over 180,000 terrorist attacks worldwide, 1970-2017.
- YouTube Video Statistics - daily trending statistics for YouTube videos.
The full list of datasets is here.
Useful laptops
A complete list of useful laptops is here.
News Digests for ML and DS
Having filtered out a large number of sources and subscriptions, I collect for you all the most significant news from the world of machine learning and artificial intelligence. You can read the digest for June here , for the July here. A complete, updated list of news digests is here.
You will learn more information about machine learning and Data Science by subscribing to my account on Habré and the Telegram channel Neuron . Do not skip future articles. In addition, I remind you - add your most useful links to comments, the coolest ones I will add to my file. Share your learning stories, life hacks and knowledge.
All success and knowledge!
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