Artificial intelligence with python cookbook : proven recipes for applying ai algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6

If you are looking to build next-generation AI solutions for work or even for your pet projects, you'll find this cookbook useful. With the help of easy-to-follow recipes, this book will take you through the advanced AI and machine learning approaches and algorithms that are required to build s...

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Bibliographic Details
Main Author: Auffarth, Ben.
Format: eBook
Language: English
Published: Birmingham : PACKT Publishing, 2020.
Subjects:
Machine learning.
Artificial intelligence.
Python (Computer program language)
elektronické knihy
electronic books
ISBN: 9781789137965
1789137969
Physical Description: 1 online resource

Cover

Table of contents

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245 1 0 |a Artificial intelligence with python cookbook :  |b proven recipes for applying ai algorithms and deep learning techniques using TensorFlow 2.x and PyTorch 1.6 
264 1 |a Birmingham :  |b PACKT Publishing,  |c 2020. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
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506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a If you are looking to build next-generation AI solutions for work or even for your pet projects, you'll find this cookbook useful. With the help of easy-to-follow recipes, this book will take you through the advanced AI and machine learning approaches and algorithms that are required to build smart models for problem-solving. 
505 0 |a Cover -- Title Page -- Copyright and Credits -- About Packt -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Artificial Intelligence in Python -- Technical requirements -- Setting up a Jupyter environment -- Getting ready -- How to do it... -- Installing libraries with Google Colab -- Self-hosting a Jupyter Notebook environment -- How it works... -- There's more... -- See also -- Getting proficient in Python for AI -- Getting ready -- How to do it... -- Obtaining the history of Jupyter commands and outputs -- Execution history -- Outputs 
505 8 |a Auto-reloading packages -- Debugging -- Timing code execution -- Displaying progress bars -- Compiling your code -- Speeding up pandas DataFrames -- Parallelizing your code -- See also -- Classifying in scikit-learn, Keras, and PyTorch -- Getting ready -- How to do it... -- Visualizing data in seaborn -- Modeling in scikit-learn -- Modeling in Keras -- Modeling in PyTorch -- How it works... -- Neural network training -- The SELU activation function -- Softmax activation -- Cross-entropy -- See also -- Modeling with Keras -- Getting ready -- How to do it... -- Data loading and preprocessing 
505 8 |a Model training -- How it works... -- Maximal information coefficient -- Data generators -- Permutation importance -- See also -- Chapter 2: Advanced Topics in Supervised Machine Learning -- Technical requirements -- Transforming data in scikit-learn -- Getting ready -- How to do it... -- Encoding ranges numerically -- Deriving higher-order features -- Combining transformations -- How it works... -- There's more... -- See also -- Predicting house prices in PyTorch -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Live decisioning customer values 
505 8 |a Getting ready -- How to do it... -- How it works... -- Active learning -- Hoeffding Tree -- Class weighting -- See also -- Battling algorithmic bias -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Forecasting CO2 time series -- Getting ready -- How to do it... -- Analyzing time series using ARIMA and SARIMA -- How it works... -- There's more... -- See also -- Chapter 3: Patterns, Outliers, and Recommendations -- Clustering market segments -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Discovering anomalies 
505 8 |a Getting ready -- How to do it... -- How it works... -- k-nearest neighbors -- Isolation forest -- Autoencoder -- See also -- Representing for similarity search -- Getting ready -- How to do it... -- Baseline -- string comparison functions -- Bag-of-characters approach -- Siamese neural network approach -- How it works... -- Recommending products -- Getting ready -- How to do it... -- How it works... -- Precision at k -- Matrix factorization -- The lightfm model -- See also -- Spotting fraudster communities -- Getting ready -- How to do it... -- Creating an adjacency matrix 
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650 0 |a Machine learning. 
650 0 |a Artificial intelligence. 
650 0 |a Python (Computer program language) 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
776 0 8 |i Print version:  |a Auffarth, Ben  |t Artificial Intelligence with Python Cookbook : Proven Recipes for Applying AI Algorithms and Deep Learning Techniques Using TensorFlow 2. x and Pytorch 1. 6  |d Birmingham : Packt Publishing, Limited,c2020  |z 9781789133967 
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