Learning plan for machine learning
| Week | What you will learn | Project | Video Links | Reading List |
|---|---|---|---|---|
| 1 | intro to ML with python libraries, using pandas to extract data | Reproducing the results in this repo | Watch this video and Complete week 1 lectures from this course | MLA: chapter 1 and Deep Learning book |
| 2 | Intro to machine learning, regression | Housing Prices Project: to predict housing prices based on previously collected data | Finish SL1 and SL2 from this course | PML:Chapter 10. ,MLA: section 1.4.1 and MLY Chapter: 28, 29. 30, 31, 32 |
| 3 | Support vector machines and ensumble learning and | Project Description: Use SVM classifiers to classify Data of the Iris dataset. you will find the Iris dataset in scikit learn datasets. You sould use all what you learned in the pase weeks like train-test splits, cross validation and grid- search to optimize the SVM classifier. Start the project using LinearSVC() and get the results then compare it with results from SVC() classifier and try to illustrate which classifier is better and why. The Project should be written in Ipynp file and it must look like a professional tutorial like the ones in machine learning mastry. The test score must be very close 100 % | Finish UL2, UL3 and UL4 from this course and Complete week 7 lectures from this course | HML Chapter 5 and MLA section 6.2 |
| 4 | Logistic regression, Intro to MLP, Deep Neural Networks, Error Analysis | Use Deep Neural Networks to classify hand digit characters in the MNIST dataset you will use a higher level library called keras with tensorflow as the backend. explore the data choose eval. metric classify the digits perform error analysis optmize the model | Complete week 1,2,3,4 Video lectures from this course | MLA: chapter 1 and Deep Learning book |
| 5 | Convolutional Neural Networks | https://www.kaggle.com/c/digit-recognizer Make an account on kaggle and then choose Kernels from the competition page and from kernels choose Notebook compare the results from Deep NN from last week with the ConvNet that you will implement this week | Week 1 | HML Chapter 13 |