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A four week study plan to get started with machine learning
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| Week 1 | |
| Revision of basic programming with Python, for loops, if-else statements, etc. Basic stuff | |
| Mathematical libraries such as Numpy, Pandas, Matplotlib. | |
| Week 2 | |
| Basic Machine Learning concepts | |
| What is the difference between Supervised and Unsupervised learning? | |
| What are Regression and Classification? | |
| How do you define a Machine Learning model? | |
| What do you mean by training and testing a model?] | |
| Week 3 | |
| In the third week, we dive deeper into the mathematics behind the techniques (like gradient descent) that we earlier discussed. | |
| How does the different training algorithms work? | |
| Week 4 | |
| Introduction to Neural Networks. | |
| Why do we need the concept of a Neural network? What's the intuition behind an artificial neuron? | |
| The McCulloh Pitts Neuron | |
| Deep Neural Networks and how they work? | |
| What are weights in a neural network? |
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