Further reading

To save you some effort, I have prepared a list of useful resources, to help you go deeper into exploring the techniques we have discussed.

Recommended books:

• Python Machine Learning - Second Edition by Sebastian Raschka and Vahid Mirjalili: https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning-second-edition 
• Building Machine Learning Systems with Python by Luis Pedro Coelho and Willi Richert: https://www.amazon.com/Building-Machine-Learning-Systems-Python/dp/1782161406 
• Data Science from Scratch: First Principles with Python by Joel Grus: https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X/ref=pd_sim_14_4?_encoding=UTF8&pd_rd_i=149190142X&pd_rd_r=506TTMZ93CK4Q4KZWDRM&pd_rd_w=5Eqf8&pd_rd_wg=1HMzv&psc=1&refRID=506TTMZ93CK4Q4KZWDRM

Recommended websites and online courses:

• Machine Learning Mastery: https://machinelearningmastery.com
• Coursera?—?Machine Learning (Andrew Ng): https://www.coursera.org/learn/machine-learning#syllabus
• Neural Networks for Machine Learning: https://www.coursera.org/learn/neural-networks