# Data Science Resources

Packet book – Data mining with python – https://github.com/PacktPublishing/Learning-Data-Mining-with-Python-Second-Edition

Introduction To Data Mining book resources – https://www-users.cs.umn.edu/~kumar001/dmbook/index.php

Course: Knowledge Discovery and Data Mining – http://www.cse.ust.hk/~leichen/courses/comp5331/

Statistical Data Mining Tutorials – https://www.autonlab.org/tutorials/list.html

Math is fun – https://www.mathsisfun.com/data/index.html

simple Logistic regression – https://www.kaggle.com/emilyhorsman/basic-logistic-regression-with-numpy

regression with 2 dimensions – http://faculty.cas.usf.edu/mbrannick/regression/Reg2IV.html

course: Introduction to ML – http://courses.washington.edu/css581/CSS%20581%20-%20Introduction%20to%20Machine%20Learning.html

Course: Machine Learning – http://cs229.stanford.edu/syllabus.html

course – ML – http://ciml.info

Neural Networks

http://www.bogotobogo.com/python/scikit-learn/Artificial-Neural-Network-ANN-1-Introduction.php

https://github.com/Einsteinish/Artificial-Neural-Networks-with-Jupyter

https://www.nnwj.de/backpropagation.html

https://mashimo.wordpress.com/2015/09/13/back-propagation-for-neural-network/

https://medium.com/technology-invention-and-more/how-to-build-a-multi-layered-neural-network-in-python-53ec3d1d326a

https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1

https://www.kdnuggets.com/2017/10/tensorflow-building-feed-forward-neural-networks-step-by-step.html

http://briandolhansky.com/blog/artificial-neural-networks-linear-regression-part-1

Book – http://neuralnetworksanddeeplearning.com/chap1.html

Book Examples – https://github.com/mnielsen/neural-networks-and-deep-learning

NPL

https://courses.engr.illinois.edu/cs546/sp2018/

https://courses.engr.illinois.edu/cs447/fa2017/syllabus.html