The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we’ll do this together using Google Colab in the browser. Join me, there’s a lot to cover here!
Published on August 31, 2018 by Carlo LepelaarsCategory AI Machine Learning Tag A.I. (Artificial Intelligence) C++ Machine Learning Python Siraj Raval
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(14 min.) Artificial Intelligence: A New Age or Another Doomsday Scenario | Kamal Fataliyev | TEDxADA (2015)
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