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Addition of extra resources #1

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Addition of extra resources #1

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Addition of free resources
EdemGold Aug 8, 2021
0109e70
Merge pull request #1 from EdemGold/EdemGold-patch-1
EdemGold Aug 8, 2021
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7 changes: 7 additions & 0 deletions README.md
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Expand Up @@ -27,6 +27,10 @@ Watch the video on YouTube for instructions:
- [ ] [Khan Academy - Statistics Probability](https://www.khanacademy.org/math/statistics-probability)
- [ ] Python
- [ ] [Python Full Course 4 Hours - FreeCodeCamp on YouTube](https://www.youtube.com/watch?v=rfscVS0vtbw)
- [ ] [Python Crash Course - Coursera](https://www.coursera.org/learn/python-crash-course)
- [ ] [python Crash Course - Coursera](https://www.coursera.org/learn/python-data)
- [ ] [Python 3.6 for total Beginers](https://www.coursera.org/learn/python-data)
- [ ] [Python Crash Course - simpilearn](https://www.youtube.com/watch?v=Yrtm7d3TJbs)
- [ ] [Advanced Python - Playlist on YouTube (Python Engineer)](https://www.youtube.com/watch?v=QLTdOEn79Rc&list=PLqnslRFeH2UqLwzS0AwKDKLrpYBKzLBy2)
- [ ] [Numpy - Free Udemy Course](https://www.udemy.com/course/deep-learning-prerequisites-the-numpy-stack-in-python/)
- [ ] Matplotlib
Expand All @@ -36,13 +40,16 @@ Watch the video on YouTube for instructions:

### 1. Basics Machine Learning
- [ ] [Coursera Free Course by Andrew Ng](https://www.coursera.org/learn/machine-learning)
- [ ] [Machine Learning crash course - edureka](https://www.youtube.com/watch?v=b2q5OFtxm6A)
- [ ] [Machine Learning Stanford Full Course on YouTube](https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN)
- [ ] [Machine Learning crash course - simplilearn](https://www.youtube.com/watch?v=9f-GarcDY58)
- [ ] [Udacity - Introduction to Machine Learning](https://www.udacity.com/course/intro-to-machine-learning--ud120)
- [ ] [Machine Learning From Scratch - Playlist on YouTube (Python Engineer)](https://www.youtube.com/watch?v=ngLyX54e1LU&list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E)
- [ ] Books (Optional and not free, but I recommend at least the first one):
- [ ] [Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow - Aurélien Géron](https://www.amazon.com/Hands-Machine-Learning-Scikit-Learn-TensorFlow/dp/1492032646/ref=sr_1_1?crid=1J69S9GKU93E4&keywords=hands+on+machine+learning+with+scikit-learn+and+tensorflow+2&qid=1584648367&sprefix=hands+o%2Caps%2C256&sr=8-1)
- [ ] [Python Machine Learning - Sebastian Raschka](https://www.amazon.com/Python-Machine-Learning-scikit-learn-TensorFlow/dp/1789955750/ref=sr_1_1?crid=L7PEHL95RXH4&keywords=python+machine+learning&qid=1584648438&sprefix=python+ma%2Caps%2C230&sr=8-1)
- [ ] [Introduction to Machine Learning with Python - Andreas Müller](https://www.amazon.com/Introduction-Machine-Learning-Python-Scientists/dp/1449369413/ref=sr_1_1?crid=WAQPG9CEM3W&keywords=introduction+to+machine+learning+with+python&qid=1584648523&sprefix=introduc%2Caps%2C238&sr=8-1)
- [ ] [Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow - Aurélien Géron -free Ebook](https://www.pdfdrive.com/hands-on-machine-learning-with-scikit-learn-and-tensorflow-concepts-tools-and-techniques-e168440497.html)

### 2. Deep Learning
- [ ] [Stanford Lecture - Convolutional Neural Networks for Visual Recognition](https://www.youtube.com/watch?v=vT1JzLTH4G4&list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)
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