book

Artificial Intelligence with Python Cookbook

Name: Artificial Intelligence with Python Cookbook
ISBN: 9781789133967

by Ritesh Kumar, Ben Auffarth

October 2020

Beginner to intermediate

468 pages

9h 39m

English

Packt Publishing

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Title Page
Copyright and Credits
Artificial Intelligence with Python Cookbook
About Packt
Why subscribe?
Contributors
About the authorAbout the reviewersPackt is searching for authors like you
Preface
Who this book is forWhat this book coversTo get the most out of this bookDownload the example code filesDownload the color imagesConventions usedSectionsGetting readyHow to do it…How it works…There's more…See alsoGet in touchReviews
Getting Started with Artificial Intelligence in Python
Technical requirementsSetting up a Jupyter environmentGetting readyHow to do it...Installing libraries with Google ColabSelf-hosting a Jupyter Notebook environmentHow it works...There's more...See alsoGetting proficient in Python for AIGetting readyHow to do it...Obtaining the history of Jupyter commands and outputsExecution historyOutputsAuto-reloading packagesDebuggingTiming code executionDisplaying progress barsCompiling your codeSpeeding up pandas DataFramesParallelizing your codeSee alsoClassifying in scikit-learn, Keras, and PyTorchGetting readyHow to do it...Visualizing data in seabornModeling in scikit-learnModeling in KerasModeling in PyTorchHow it works...Neural network trainingThe SELU activation functionSoftmax activationCross-entropySee alsoModeling with KerasGetting readyHow to do it...Data loading and preprocessingModel trainingHow it works...Maximal information coefficientData generatorsPermutation importanceSee also
Advanced Topics in Supervised Machine Learning
Technical requirementsTransforming data in scikit-learnGetting readyHow to do it...Encoding ranges numericallyDeriving higher-order featuresCombining transformationsHow it works...There's more...See alsoPredicting house prices in PyTorchGetting readyHow to do it...How it works...There's more...See alsoLive decisioning customer valuesGetting readyHow to do it...How it works...Active learningHoeffding TreeClass weightingSee alsoBattling algorithmic biasGetting readyHow to do it...How it works...There's more...See alsoForecasting CO2 time seriesGetting readyHow to do it...Analyzing time series using ARIMA and SARIMAHow it works...There's more...See also
Patterns, Outliers, and Recommendations
Clustering market segmentsGetting readyHow to do it...How it works...There's more...See alsoDiscovering anomaliesGetting readyHow to do it...How it works...k-nearest neighborsIsolation forestAutoencoderSee alsoRepresenting for similarity searchGetting readyHow to do it...Baseline – string comparison functionsBag-of-characters approachSiamese neural network approachHow it works...Recommending productsGetting readyHow to do it...How it works...Precision at kMatrix factorizationThe lightfm modelSee alsoSpotting fraudster communitiesGetting readyHow to do it...Creating an adjacency matrixCommunity detection algorithmsEvaluating the communitiesHow it works...Graph community algorithmsLouvain algorithmGirvan–Newman algorithmInformation entropyThere's more...See also
Probabilistic Modeling
Technical requirementsPredicting stock prices with confidenceGetting readyHow to do it...How it works...FeaturizationPlatt scalingIsotonic regressionNaive BayesSee alsoEstimating customer lifetime valueGetting readyHow to do it...How it works...The BG/NBD modelThe Gamma-Gamma modelSee alsoDiagnosing a diseaseGetting readyHow to do it...How it works...Aleatoric uncertaintyNegative log-likelihoodBernoulli distributionMetricsSee alsoStopping credit defaultsGetting readyHow to do it...How it works...Epistemic uncertaintySee also
Heuristic Search Techniques and Logical Inference
Making decisions based on knowledgeGetting readyHow to do it...Logical reasoningKnowledge embeddingHow it works...Logical reasoningLogic proversKnowledge embeddingGraph embedding with WalkletsSee alsoSolving the n-queens problemGetting readyHow to do it...Genetic algorithm Particle swarm optimizationSAT solverHow it works...Genetic algorithmParticle swarm optimizationSAT solverSee alsoFinding the shortest bus routeGetting readyHow to do it...Simulated annealingAnt colony optimizationHow it works...Simulated annealingAnt colony optimizationSee alsoSimulating the spread of a diseaseGetting readyHow to do it...How it works...There's more...See alsoWriting a chess engine with Monte Carlo tree searchGetting readyHow to do it...Tree searchImplementing a nodePlaying chessHow it works...There's more...See also

Deep Reinforcement Learning
Technical requirementsOptimizing a websiteHow to do it...How it works...See alsoControlling a cartpoleGetting readyHow to do it...How it works...There's more...Watching our agents in the environmentUsing the RLlib librarySee also Playing blackjackGetting readyHow to do it...How it works...See also
Advanced Image Applications
Technical requirementsRecognizing clothing itemsGetting readyHow to do it...Difference of GaussiansMultilayer perceptronLeNet5MobileNet transfer learningHow it works...Difference of GaussianLeNet5MobileNet transfer learningSee alsoGenerating imagesGetting readyHow to do it...How it works...See alsoEncoding images and styleGetting readyHow to do it...How it works...See also
Working with Moving Images
Technical requirementsLocalizing objectsGetting readyHow to do it...How it works...There's more...See alsoFaking videosGetting readyHow to do it...How it works...See alsoDeep fakesDetection of deep fakes
Deep Learning in Audio and Speech
Technical requirementsRecognizing voice commandsGetting readyHow to do it...How it works...See alsoSynthesizing speech from textGetting readyHow to do it...How it works...Deep Convolutional Networks with Guided AttentionWaveGANThere's more...See alsoGenerating melodiesGetting readyHow to do it...How it works...See also
Natural Language Processing
Technical requirementsClassifying newsgroupsGetting readyHow to do it...Bag-of-wordsWord embeddingsCustom word embeddingsHow it works...The CBOW algorithmTFIDFThere's more...See alsoChatting to usersGetting readyHow to do it...How it works...ELIZAEywaSee alsoTranslating a text from English to GermanGetting readyHow to do it...How it works...There's more...See alsoWriting a popular novelGetting readyHow to do it...How it works...See also
Artificial Intelligence in Production
Technical requirementsVisualizing model resultsGetting readyHow to do it...Streamlit hello-worldCreating our data appHow it works...See alsoServing a model for live decisioningGetting readyHow to do it...How it works...MonitoringSee alsoSecuring a model against attackGetting readyHow to do it...How it works...Differential privacyPrivate aggregation of teacher ensemblesSee also
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Overview

Dive into the world of artificial intelligence development with "Artificial Intelligence with Python Cookbook." This book offers hands-on recipes that enable you to solve a variety of complex problems using AI and machine learning. Through practical examples, you'll master techniques spanning from basic data handling to advanced deep learning utilizing TensorFlow and PyTorch.

What this Book will help me do

Optimize AI project workflows by learning efficient data preprocessing methods.
Gain insights into advanced AI techniques such as adversarial autoencoders and probabilistic modeling.
Develop deep learning models that analyze and interpret text, images, and audio data.
Apply cutting-edge AI algorithms like style transfer, GANs, and reinforcement learning.
Learn to deploy machine learning solutions as efficient, scalable microservices.

Author(s)

None Kumar and Ben Auffarth are respected experts in artificial intelligence and Python programming. They bring a wealth of experience from years of applying AI solutions in real-world applications. None Kumar specializes in deep learning and has contributed to notable AI advancements. Ben Auffarth is an experienced data scientist with a knack for making complex AI topics accessible.

Who is it for?

This book is perfect for Python developers, data scientists, and machine learning engineers aiming to expand their expertise in AI. Readers should have basic Python and machine learning knowledge. It's ideal for those looking to effectively implement AI projects in professional or personal contexts and grasp cutting-edge AI techniques.

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