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* Resources added * Updated projects.md Fixes dipakkr#497
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## Table of Contents | ||
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1. [Machine Learning](#1-machine-learning) | ||
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- [Where to Start in ML ? ](#1.1-where-to-start-in-ml) | ||
- [Online Courses](#1.2-online-courses) | ||
- [Research Paper](#1.3-research-paper) | ||
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- [Online Courses](#2.2-online-courses) | ||
- [Research Paper](#2.3-research-paper) | ||
- [Top Github Repositories](#2.4-top-github-repositories) | ||
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3. [DataSets](#2-datasets) | ||
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4. [Data Science Conference](#4-data-science-confs) | ||
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# 1. **Machine Learning** | ||
## 1.1 Where to Start in ML? | ||
1) Python | ||
1) Python | ||
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- [Basics of Python](https://www.youtube.com/playlist?list=PLQVvvaa0QuDe8XSftW-RAxdo6OmaeL85M) | ||
- [More in Python](https://www.youtube.com/playlist?list=PL-osiE80TeTt2d9bfVyTiXJA-UTHn6WwU) | ||
- [Python for ML](https://www.udemy.com/python-for-data-science-and-machine-learning-bootcamp) | ||
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2) Maths for ML | ||
- [Statistics and Probability](https://www.khanacademy.org/math/statistics-probability) | ||
- [Partial Derivatives](https://www.khanacademy.org/math/multivariable-calculus/multivariable-derivatives) | ||
- [Derivatives](https://www.khanacademy.org/math/calculus-1/cs1-derivatives-definition-and-basic-rules) | ||
- [Linear Algebra](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8) | ||
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3) Intro to ML | ||
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- [Machine Learning Recipes with Josh Gordon](https://www.youtube.com/playlist?list=PLOU2XLYxmsIIuiBfYad6rFYQU_jL2ryal) | ||
- [Into to ML](https://in.udacity.com/course/intro-to-machine-learning--ud120-india) | ||
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- [[email protected]](http://course.fast.ai/start.html) | ||
- [Deep Learning Specialization](https://www.coursera.org/specializations/deep-learning) | ||
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2) | ||
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# 3. **DataSets** | ||
- [MNIST Dataset for Digit Recogniser](http://yann.lecun.com/exdb/mnist/) | ||
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## COMING SOON | ||
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# 5. **Celebrities in ML and AI world** | ||
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