New Book Release: A Primer to the 42 Most commonly used Machine Learning Algorithms (With Code Samples)

This book introduces you to the 42 most commonly used machine learning algorithms in an understandable way. Each algorithm is also demonstrated with a simple code example in Python.

The following algorithms are covered in this book:

• ADABOOST
• ADAM OPTIMIZATION
• AGGLOMERATIVE CLUSTERING
• ARMA/ARIMA MODEL
• BERT
• CONVOLUTIONAL NEURAL NETWORK
• DBSCAN
• DECISION TREE
• DEEP Q-LEARNING
• EFFICIENTNET
• FACTOR ANALYSIS OF CORRESPONDENCES
• GAN
• GMM
• GPT-3
• GRADIENT BOOSTING MACHINE
• GRADIENT DESCENT
• GRAPH NEURAL NETWORKS
• HIERARCHICAL CLUSTERING
• HIDDEN MARKOV MODEL (HMM)
• INDEPENDENT COMPONENT ANALYSIS
• ISOLATION FOREST
• K-MEANS
• K-NEAREST NEIGHBOUR
• LINEAR REGRESSION
• LOGISTIC REGRESSION
• LSTM
• MEAN SHIFT
• MOBILENET
• MONTE CARLO ALGORITHM
• MULTIMODAL PARALLEL NETWORK
• NAIVE BAYES CLASSIFIERS
• PROXIMAL POLICY OPTIMIZATION
• PRINCIPAL COMPONENT ANALYSIS
• Q-LEARNING
• RANDOM FORESTS
• RECURRENT NEURAL NETWORK
• RESNET
• SPATIAL TEMPORAL GRAPH CONVOLUTIONAL NETWORKS
• STOCHASTIC GRADIENT DESCENT
• SUPPORT VECTOR MACHINE
• WAVENET
• XGBOOST

The Book is available on Amazon: https://www.amazon.com/dp/B0BT911HDM

Thurn-und-Taxis-Platz 6 (Nextower)
60313 Frankfurt am Main
Telefon: 069 257375160
E-Mail: murat.durmus@aisoma.de

Murat Durmus is CEO and founder of AISOMA (a Frankfurt am Main (Germany) based company specializing in AI-based technology development and consulting) and Author of the book "Mindful AI - Reflections on Artificial Intelligence" and "INSIDE ALAN TURING."

This release was published on openPR.