From Scratch, let's start Deep Learning with Python (plus Text Processing, pr...Kiyoshi Ogawa
This is the third time of reading club on "Deep Learning". The book using Python to program. Mainly, the text deal with image processing. So I add text processing references, privately.There are thirteen Oreilly's Books about Computer, data science, machine learning, Image processing, text processing and Python. You can understand whatever the direction of interest are different.
From Scratch, let's start Deep Learning with Python (plus Text Processing, pr...Kiyoshi Ogawa
This is the third time of reading club on "Deep Learning". The book using Python to program. Mainly, the text deal with image processing. So I add text processing references, privately.There are thirteen Oreilly's Books about Computer, data science, machine learning, Image processing, text processing and Python. You can understand whatever the direction of interest are different.
Introducton to Convolutional Nerural Network with TensorFlowEtsuji Nakai
Explaining basic mechanism of the Convolutional Neural Network with sample TesnsorFlow codes.
Sample codes: https://github.com/enakai00/cnn_introduction
Effective Numerical Computation in NumPy and SciPyKimikazu Kato
This document provides an overview of effective numerical computation in NumPy and SciPy. It discusses how Python can be used for numerical computation tasks like differential equations, simulations, and machine learning. While Python is initially slower than languages like C, libraries like NumPy and SciPy allow Python code to achieve sufficient speed through techniques like broadcasting, indexing, and using sparse matrix representations. The document provides examples of how to efficiently perform tasks like applying functions element-wise to sparse matrices and calculating norms. It also presents a case study for efficiently computing a formula that appears in a machine learning paper using different sparse matrix representations in SciPy.