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 1 | # How to get started with ML
 2 | 
 3 | This my recommended study guide to get started with Machine Learning.
 4 | 
 5 | Watch the video on [YouTube](https://youtu.be/wtolixa9XTg).
 6 | 
 7 | ## 1. Math
 8 | 
 9 | Learn some math basics! Focus only on these topics, then come back later in case you need to learn more.
10 | 
11 |  * [Khan Academy - Multivariable Calculus](https://www.khanacademy.org/math/multivariable-calculus)
12 |  * [Khan Academy - Differential Equations](https://www.khanacademy.org/math/differential-equations)
13 |  * [Khan Academy - Linear Algebra](https://www.khanacademy.org/math/linear-algebra)
14 |  * [Khan Academy - Statistics Probability](https://www.khanacademy.org/math/statistics-probability)
15 |  * [Optional: 3Blue1Brown - Essence of Linear Algebra](https://www.3blue1brown.com/essence-of-linear-algebra-page/)
16 |  
17 | ## 2. Learn Python
18 | 
19 | * [4h Beginner Course](https://youtu.be/rfscVS0vtbw)
20 | * [6h Intermediate Python Programming Course](https://youtu.be/HGOBQPFzWKo)
21 | 
22 | ## 3. Learn The ML Tech Stack:
23 | 
24 | * NumPy:  [1h NumPy Crash Course](https://youtu.be/9JUAPgtkKpI)
25 | * Pandas: [1h Pandas Crash Course](https://youtu.be/vmEHCJofslg)
26 | * Matplotlib: [1h Matplotlib Crash Course Course](https://youtu.be/3Xc3CA655Y4)
27 | 
28 | (Scikit-Learn and TensorFlow are taught in step 4. PyTorch is optional, maybe in step 7)
29 | 
30 | ## 4. Machine Learning Courses
31 | 
32 | * [Machine Learning Specialization Andrew Ng | Coursera](https://www.coursera.org/specializations/machine-learning-introduction) (3 Courses)
33 | * Optional: [Machine Learning From Scratch](https://youtube.com/playlist?list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E)
34 | 
35 | ## 5. Hands-on Data Preparation
36 | 
37 | * [Kaggle Intro to Machine Learning](https://www.kaggle.com/learn/intro-to-machine-learning)
38 | * [Kaggle Intermediate Machine Learning](https://www.kaggle.com/learn/intermediate-machine-learning)
39 | 
40 | ## 6. Practise!
41 | 
42 | Solve Challenges and build your own projects with datasets from [Kaggle.com](Kaggle.com).
43 | 
44 | ## 7. Specialize & Create Blog
45 | 
46 | * Specialize in one field (e.g. Computer Vision, NLP, etc.) 
47 | * Look at requirements in corresponding job descriptions and learn those skills
48 | * Tip: Create a blog and share tutorials and what you have learned!
49 | 
50 | ## Books
51 | If you prefer learning with books, these are great recommendations:
52 | 
53 | * [Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow](https://www.oreilly.com/library/view/hands-on-machine-learning/9781492032632/)
54 | * [Machine Learning with PyTorch and Scikit-Learn](https://www.packtpub.com/product/machine-learning-with-pytorch-and-scikit-learn/9781801819312)
55 | 


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