Machine Learning For Absolute Beginners a Step by Step guide Algorithms For Supervised and Unsupervised Learning With Real World Applications by Raymond Kazuya

Author:Raymond Kazuya
Language: eng
Format: epub
Tags: Machine Learning, Data Anayltics & Data Science, Algorithms, Singularity, Supervised Learning, Unsupervised Learning, Artificial Intelligence, Random Forest, Neural Networks, Deep Learning, Python, Scikit-Learn Intelligent Systems, Decision Tree, Pattern Recognition
Publisher: Raymond Kazuya
Published: 2017-12-16T16:00:00+00:00

When an engineer is tasked with selecting an algorithm for a specific application, he may choose to compare various algorithms experimentally to decide which one is best suited for the application. However, a large amount of time needs to be invested by the engineer in collecting training data and tuning the algorithm. If provided with a large number of resources, it is advisable to spend more time collecting data than spending time on tuning the algorithm because the latter is extremely tedious. The most commonly used learning algorithms are neural networks, nearest neighbor algorithms, linear and logistic regressions, support vector machines and decision trees.

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