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Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python

(ebook) (audiobook) (audiobook) Książka w języku 1
Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, Man Chon (Kevin) U, Gavin Hackeling, Sarah Guido, Mikhail Korobov, Andreas Mueller, Aman Madaan - okladka książki

Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, Man Chon (Kevin) U, Gavin Hackeling, Sarah Guido, Mikhail Korobov, Andreas Mueller, Aman Madaan - okladka książki

Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, Man Chon (Kevin) U, Gavin Hackeling, Sarah Guido, Mikhail Korobov, Andreas Mueller, Aman Madaan - audiobook MP3

Advanced Machine Learning with Python. Solve challenging data science problems by mastering cutting-edge machine learning techniques in Python Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, Man Chon (Kevin) U, Gavin Hackeling, Sarah Guido, Mikhail Korobov, Andreas Mueller, Aman Madaan - audiobook CD

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Bądź pierwszym, który oceni tę książkę
Stron:
278
Dostępne formaty:
     PDF
     ePub
     Mobi
Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.


The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.

This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.

By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering.

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O autorach książki

Victor Marak is a security researcher, an electronic musician, and a world backpacker. He is a college dropout and an autodidact, and he loves working on interesting subjects such as medieval music composition, demonology, DSP electronics, and psychology. He has worked for start-ups, mid-tier, and fortune 500 companies with 5 years of experience in anti-virus technologies and malware research. He was into music production prior to joining the anti-malware industry, and his solo projects are on the world's largest electronic dance music market— Beatport, as well as other major retailers like iTunes, Amazon and Traxxsource. He is in perpetual backpacking mode, set to globe-trotting, especially to his favorite countries in Europe and Russia. He can be found hanging around in the wrong social networks - LinkedIn and Quora. This is his first book.
Nishant Shukla is a computer scientist with a passion for mathematics. Throughout the years, he has worked for a handful of start-ups and large corporations including WillowTree Apps, Microsoft, Facebook, and Foursquare. Stepping into the world of Haskell was his excuse for better understanding Category Theory at first, but eventually, he found himself immersed in the language. His semester-long introductory Haskell course in the engineering school at the University of Virginia (https://shuklan.com/haskell) has been accessed by individuals from over 154 countries around the world, gathering over 45,000 unique visitors. Besides Haskell, he is a proponent of decentralized Internet and open source software. His academic research in the fields of Machine Learning, Neural Networks, and Computer Vision aim to supply a fundamental contribution to the world of computing.
https://www.linkedin.com/profile/view?id=86335697

Gavin Hackeling develops machine learning services for large-scale documents and image classification at an advertising network in New York. He received his Master's degree from New York University's Interactive Telecommunications Program, and his Bachelor's degree from the University of North Carolina.

Sarah Guido jest analitykiem danych. Pracowała w kilku w start-upach. Jest ceniona za znakomite wystąpienia na prestiżowych konferencjach.

04/04/2019-DO NOT CONTACT. Turns out he has been contacted 3 times before I contacted him. It is only now that I have added him to contact list. Please make sure you update your contacts!

Victor Marak, Nishant Shukla, John Hearty, Jeffery Yee, Man Chon (Kevin) U, Gavin Hackeling, Sarah Guido, Mikhail Korobov, Andreas Mueller, Aman Madaan - pozostałe książki

Packt Publishing - inne książki

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