├── images
├── dl.jpg
├── dl.png
├── la.png
├── ml.jpg
├── py.png
├── algo.png
├── data.jpg
├── funml.jpg
└── mlcourseai.jpg
├── .github
└── FUNDING.yml
├── LICENSE
└── README.md
/images/dl.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/dl.jpg
--------------------------------------------------------------------------------
/images/dl.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/dl.png
--------------------------------------------------------------------------------
/images/la.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/la.png
--------------------------------------------------------------------------------
/images/ml.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/ml.jpg
--------------------------------------------------------------------------------
/images/py.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/py.png
--------------------------------------------------------------------------------
/images/algo.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/algo.png
--------------------------------------------------------------------------------
/images/data.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/data.jpg
--------------------------------------------------------------------------------
/images/funml.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/funml.jpg
--------------------------------------------------------------------------------
/images/mlcourseai.jpg:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/frontbenchHQ/Data-Science-Free/HEAD/images/mlcourseai.jpg
--------------------------------------------------------------------------------
/.github/FUNDING.yml:
--------------------------------------------------------------------------------
1 | # These are supported funding model platforms
2 |
3 | github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2]
4 | patreon: # Replace with a single Patreon username
5 | open_collective: # Replace with a single Open Collective username
6 | ko_fi: # Replace with a single Ko-fi username
7 | tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
8 | community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
9 | liberapay: # Replace with a single Liberapay username
10 | issuehunt: # Replace with a single IssueHunt username
11 | otechie: # Replace with a single Otechie username
12 | custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2']
13 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2019
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 |
2 | 
3 |
4 |
5 | A collection of awesome manuals, blogs, cheats, resources and more.
6 |
7 |
8 |
9 |
10 |
11 | 
12 |
13 |
14 |
15 | 
16 |
17 |
18 |
19 | 
20 |
21 |
22 |
23 | 
24 |
25 |
26 |
27 | 
28 |
29 |
30 |
31 |
32 | Created by Shubham Kumar
33 |
34 |
35 |
36 | # Show your support by giving :octocat: a :star:
37 | **DISCLAIMER:** ***This is for absolute beginners, no experience needed.***
38 |
39 | ## Table of Contents
40 |
41 | * [Python](#python)
42 | * [Pandas](#pandas)
43 | * [Algorithms in Python](#algorithms-in-python)
44 | * [Practice Python](#practice-python)
45 | * [Calculus](#calculus)
46 | * [Linear Algebra](#linear-algebra)
47 | * [Algorithms in Python](#algorithms-in-python)
48 | * [Probability & Stats](#probability-and-statistics)
49 | * [Statistical Learning](#statistical-learning)
50 | * [Machine Learning](#machine-learning)
51 | * [Practice ML](#practice-ml)
52 | * [Deep Learning](#deep-learning)
53 | * [AI Projects](#ai-projects)
54 | * [Medium Blog Posts](#AWESOME-BLOG-POSTS-ON-MEDIUM)
55 | * [Playgrounds](#playgrounds)
56 | * [Research Papers](#research-papers)
57 | * [Interview Questions](#interview-questions)
58 | * [Top Rated Courses](#top-rated-courses)
59 | * [Blogs to Follow](#blogs-to-follow)
60 |
61 |
62 | ## PYTHON
63 |
64 | 
65 |
66 |
67 | * **Python 3 tutorial by Programiz** [Here](https://www.programiz.com/python-programming/tutorial)
68 |
69 | * **Introduction to Python 3** [Sentdex](https://www.youtube.com/watch?v=eXBD2bB9-RA&list=PLQVvvaa0QuDeAams7fkdcwOGBpGdHpXln)
70 |
71 | * **Quantative Economics with Python** [Here](https://lectures.quantecon.org/py/)
72 |
73 | * **Python Data science handbook** [Chapter 1-4](https://github.com/jakevdp/PythonDataScienceHandbook/blob/8a34a4f653bdbdc01415a94dc20d4e9b97438965/notebooks/Index.ipynb)
74 |
75 | * **Python for Data Analysis** [2nd Edition](https://github.com/wesm/pydata-book)
76 |
77 | * **Learning Python 5th edition, oreilly publication by** [Mark Lutz](https://drive.google.com/file/d/14ayuNFEo9VZ-xstgXlyMgDFHoAgrGqJU/view?usp=sharing) **(LONG VERSION)**
78 |
79 | * **Python by** [Scipy](https://scipython.com/book/)
80 |
81 | * **Python Ebooks on** [Google Drive](https://drive.google.com/open?id=0ByWO0aO1eI_MZ19fbVV3YS1hckk)
82 |
83 | ## PANDAS
84 |
85 | * **Pandas & Data Analysis by [mlcourse.ai](https://www.youtube.com/watch?v=fwWCw_cE5aI&feature=youtu.be)** (Video)
86 |
87 | * **Pandas by** [Pydata](https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html)
88 |
89 | * **Effective Pandas** [GitHub](https://github.com/TomAugspurger/effective-pandas)
90 |
91 | * **Pandas** [Cheatsheets](https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf)
92 |
93 | * **Pandas Data School** [Videos](https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y)
94 |
95 | ## ALGORITHMS IN PYTHON
96 |
97 | 
98 |
99 | * **Python & Algorithms 2.0 by Marina Wahl** [Pdf](https://drive.google.com/file/d/1rR0GSEAqVtFDWRDdK1NLEJvc8oKC94PT/view?usp=sharing)
100 |
101 | * **Udacity** [Course](https://eu.udacity.com/course/data-structures-and-algorithms-in-python--ud513)
102 |
103 | * **Another good resource** [Here](http://interactivepython.org/runestone/static/pythonds/index.html)
104 |
105 | * **Visualising algorithms through animation** [Visit](https://visualgo.net/en)
106 |
107 | ## PRACTICE PYTHON
108 |
109 | * [Project based](https://github.com/tuvtran/project-based-learning#python)
110 |
111 | * [Project Euler](https://projecteuler.net/)
112 |
113 | ## CALCULUS
114 |
115 | * **Essence of Calculus** [3Blue1Brown PlayList](https://www.youtube.com/watch?v=WUvTyaaNkzM&list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr)
116 |
117 | * **Khan Academy calculus-1** [Here](https://www.khanacademy.org/math/calculus-1)
118 |
119 | * **Khan Academy calculus-2** [Here](https://www.khanacademy.org/math/calculus-2)
120 |
121 | * **Khan Academy multivariable calculus** [Here](https://www.khanacademy.org/math/multivariable-calculus)
122 |
123 | ## LINEAR ALGEBRA
124 |
125 | 
126 |
127 |
128 | * **Manga Guide to Linear Algebre** [Google Drive](https://drive.google.com/file/d/1sdnIBqPjSgPzitrInV0roHTEJ856ntYe/view?usp=sharing)
129 |
130 | * **3Blue1Brown** [PlayList](https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
131 |
132 | * **Khan Academy** [Linear algebra](https://www.khanacademy.org/math/linear-algebra)
133 |
134 | * **UBC Maths by James B. Carrell** [Here](https://www.math.ubc.ca/~carrell/NB.pdf)
135 |
136 | * **MIT** [Linear algebra](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8)
137 |
138 |
139 | ## PROBABILITY AND STATISTICS
140 |
141 | * **Khan Academy** [Course](https://www.khanacademy.org/math/statistics-probability)
142 |
143 | * **Think Stats** [Pdf](http://greenteapress.com/thinkstats/thinkstats.pdf)
144 |
145 | * **Probability** [Cheat sheet](http://www.wzchen.com/probability-cheatsheet/)
146 |
147 | * **Bayesian-Methods-for-Hackers** [Here](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/)
148 |
149 | ## STATISTICAL LEARNING
150 |
151 | * **An Introduction to Statistical Learning** [Essential](https://www-bcf.usc.edu/~gareth/ISL/index.html)
152 |
153 | * **Elements of Statistical Learning Stanford** [Extremely useful](https://web.stanford.edu/~hastie/ElemStatLearn/)
154 |
155 | ## MACHINE LEARNING
156 |
157 | 
158 |
159 |
160 | * **Machine Learning: An Algorithmic Perspective** [Here](https://doc.lagout.org/science/Artificial%20Intelligence/Machine%20learning/Machine%20Learning_%20An%20Algorithmic%20Perspective%20%282nd%20ed.%29%20%5BMarsland%202014-10-08%5D.pdf)
161 |
162 | * **Practical Machine Learning Tutorial with Python** [Sentdex](https://www.youtube.com/watch?v=OGxgnH8y2NM&list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v)
163 |
164 | * **Stanford - AndrewNg Course** [YouTube](https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN)
165 |
166 | * **Jason Mayes (Google Engineer ML Class 101)** [Slides](https://docs.google.com/presentation/d/1kSuQyW5DTnkVaZEjGYCkfOxvzCqGEFzWBy4e9Uedd9k/mobilepresent?slide=id.g168a3288f7_0_58)
167 |
168 | * **Ebooks for ML on** [Google Drive](https://drive.google.com/drive/folders/0ByWO0aO1eI_Md1JGZW9NSDFpQ1U?usp=sharing)
169 |
170 | * **More Ebooks on** [Google Drive](https://drive.google.com/open?id=1gmW2K_VAQrXPWAfgQcg-3umt5ipV7-G9)
171 |
172 | * **Manning publication books on** [Google Drive](https://drive.google.com/open?id=1yXZ1HgyQ7yPUJI8cC7ZnTWi0BAbxq_Kg)
173 |
174 | * **Cheat Sheets for ML, DeepL, AI** [Google Drive](https://drive.google.com/open?id=1qYgzm4oTVYIR_iEsT4ZW9l9o3GUMSzYG)
175 |
176 | * **Google Machine Learning crash course using Tensorflow (Not for Beginners)** [Here](https://developers.google.com/machine-learning/crash-course/)
177 |
178 | * **Reinforcement Learning Book by Andrew Barto and Richard S. Sutton** [Google Drive](https://drive.google.com/file/d/1OFquNBwdPxFFFbxCixBDHYUEmnbimegH/view?usp=sharing)
179 |
180 | * **Stanford's CS 229 Machine Learning** [VIP Cheatsheet](https://github.com/afshinea/stanford-cs-229-machine-learning)
181 |
182 | ## PRACTICE ML
183 |
184 | * **Home for Data Science -** [Kaggle](https://www.kaggle.com/)
185 |
186 | ## DEEP LEARNING
187 |
188 | 
189 |
190 |
191 | * **Grokking Deep Learning by Andrew Trask**
192 |
193 | * **Practical Deep Learning for Coders** [Fast-ai](https://course.fast.ai/)
194 |
195 | * **MIT Deep Learning** [Lex-Fridman](https://www.youtube.com/watch?v=O5xeyoRL95U&list=PLrAXtmErZgOeiKm4sgNOknGvNjby9efdf)
196 |
197 | * **MIT 6.S191: Introduction to Deep Learning** [Alexander-Amini](https://www.youtube.com/playlist?list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI)
198 |
199 | * **Demystifying RL** [Intel AI](https://www.intel.ai/demystifying-deep-reinforcement-learning/#gs.0tu98m)
200 |
201 | * **Deep RL Bootcamp** [Berkeley CA](https://sites.google.com/view/deep-rl-bootcamp/lectures)
202 |
203 | ## AI PROJECTS
204 |
205 | * **Plant Disease Detector using Pytorch & fastai** [Visit](https://github.com/imskr/Plant_Disease_Detection)
206 |
207 | * **Implement a Pong-playing agent** [Pong from Pixels](http://karpathy.github.io/2016/05/31/rl/)
208 |
209 | * **Flappy-Bird Playing agent in** [JavaScript](https://github.com/imskr/Flappy-Bird-AI)
210 |
211 | ## AWESOME BLOG POSTS ON MEDIUM
212 |
213 | * **Simple Reinforcement Learning with Tensorflow series by** [Arthur Juliani](https://medium.com/emergent-future/simple-reinforcement-learning-with-tensorflow-part-0-q-learning-with-tables-and-neural-networks-d195264329d0)
214 |
215 | * **Machine Learning for Humans by** [Vishal Maini](https://medium.com/machine-learning-for-humans/why-machine-learning-matters-6164faf1df12)
216 |
217 | ## PLAYGROUNDS
218 |
219 | * **Tensorflow [Playground](https://playground.tensorflow.org/)**
220 |
221 | * **Machine Learning [Playground](http://ml-playground.com/)**
222 |
223 |
224 |
225 | ## RESEARCH PAPERS
226 |
227 | * **[PAPERS WITH CODE](https://paperswithcode.com/)**
228 |
229 | ## INTERVIEW QUESTIONS
230 |
231 | * **100 Data Science Interview Questions and** [Answers](https://www.dezyre.com/article/100-data-science-interview-questions-and-answers-general-for-2018/184)
232 |
233 | * **40 Interview Questions asked at startups in Machine Learning** [Here](https://www.analyticsvidhya.com/blog/2016/09/40-interview-questions-asked-at-startups-in-machine-learning-data-science/)
234 |
235 | * **Top 100 Data science interview** [Questions](http://nitin-panwar.github.io/Top-100-Data-science-interview-questions/?utm_campaign=News&utm_medium=Community&utm_source=DataCamp.com)
236 |
237 | * **109 Data Science Interview Questions and Answers for 2019 on** [Springboard](https://www.springboard.com/blog/data-science-interview-questions/)
238 |
239 | * **111 Data Science Interview Questions with Detailed Answers** [Here](https://rpubs.com/JDAHAN/172473)
240 |
241 | ## TOP RATED COURSES
242 |
243 | 
244 |
245 | * **Open Machine Learning Course [mlcourse.ai](https://mlcourse.ai/)**
246 |
247 | * **CS294-158 Deep Unsupervised Learning [Spring 2019](https://sites.google.com/view/berkeley-cs294-158-sp19/home)**
248 |
249 | * **UC Berkeley CS294-112 [Deep Reinforcement Learning](http://rail.eecs.berkeley.edu/deeprlcourse/)**
250 |
251 | * **UCL Course on [RL](http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html)**
252 |
253 | * **CS109 Data Science Course - [Harvard](http://cs109.github.io/2015/pages/videos.html)**
254 |
255 | * **Python for Data Science and Machine Learning Bootcamp - [Udemy](https://www.udemy.com/course/python-for-data-science-and-machine-learning-bootcamp/?LSNPUBID=OyHlmBp2G0c&ranEAID=OyHlmBp2G0c&ranMID=39197&ranSiteID=OyHlmBp2G0c-vQFHeLPpk94Hgv3dq6AX0A&utm_medium=udemyads&utm_source=aff-campaign) (Paid)**
256 |
257 | * **Introduction to Data Science - [Metis](https://www.thisismetis.com/courses/introduction-to-data-science?utm_source=LDS&utm_medium=affiliate&utm_campaign=LDS2019affiliate) (Paid)**
258 |
259 | ## Blogs to Read
260 |
261 | 
262 |
263 | * **Machine Learning for Everyone** [Blog](https://vas3k.com/blog/machine_learning/)
264 |
265 | * **[KDNuggets](https://www.kdnuggets.com/)**
266 |
267 | * **[Data Science Plus](https://datascienceplus.com/)**
268 |
269 | * **[Analytics Vidhya](https://www.analyticsvidhya.com/)**
270 |
271 | * **[Towards Data Science](https://towardsdatascience.com/)**
272 |
273 |
274 |
275 |
276 | ## Contributors ✨
277 |
278 |
300 |
301 |
302 |
303 |
304 |
305 |
306 |
307 | >You take the blue pill, the story ends. You wake up in your
308 | >bed and believe whatever you want to believe. You take the
309 | >red pill, you stay in Wonderland, and I show you how deep
310 | >the rabbit hole goes.” — Morpheus
311 |
312 |
313 |
314 | 
315 |
316 |
317 |
318 |
--------------------------------------------------------------------------------
