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About Machine Learning Theory and Applications
This document provides an overview of machine learning theory and applications using Python on classical and quantum machines. It introduces various machine learning concepts including supervised, unsupervised, and reinforcement learning. It discusses essential Python tools for machine learning like Scikit-learn, TensorFlow, Keras and PyTorch. It also introduces HephAIstos, a library for running machine learning workloads on CPUs, GPUs and quantum processors. The document contains several chapters covering topics like feature engineering, machine learning algorithms and their applications.
Detailed Information
| Author: | ['negrytux'] |
|---|---|
| Publication Year: | 2024 |
| Pages: | 510 |
| Language: | English |
| Format: | |
| Price: | FREE |
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