Topic 20 – Introduction to Applied Machine Learning

Why do I need to learn about applied machine learning?

Machine learning has solved many important difficult problems recently. A few of them are speech recognition, speech synthesis, image recognition, autonomous driving and chat bots.
Nowadays a key skill of software developer is the ability to use machine learning algorithms solve real-world problems.

What can I do after finishing learning about applied machine learning ?

You will be to create software that could recognize speech, recognize a face, translate text to speech, translate a sentence from English to French, answer a customer's question.

That sounds useful! What should I do now?

Please attend this free "Machine Learning (Coursera)" course and audit this "Applied Machine Learning in Python (Coursera)" course first.
At the same time, please read
- this "Aurelien Geron (2017). Hands-On Machine Learning with Scikit Learn and TensorFlow. O’Reilly Media" book and
- this "Brett Lantz (2015). Machine Learning With R. 2nd Edition. Packt Publishing" book.

After that please audit these "Deep Learning Specialization" courses.
At the same time, please read
- this "Francois Chollet (2018). Deep Learning with Python. Manning Publications" book and
- this "Michael Nielsen (2015). Neural Networks and Deep Learning. Determination Press" book.

After that please read this "Christopher M. Bishop (2006). Pattern Recognition and Machine Learning. Springer" book.
After finishing reading these books please click Topic 21 - Introduction to Applied Computer Vision and Natural Language Processing to continue.

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