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Machine Learning, an integral part of Artificial Intelligence

#artificialintelligence

This is just the beginning. Technology, which promises to bring huge changes to the world in coming years, is nothing but Machine Learning. It is an essential part of Artificial Intelligence research and gained the highest limelight in business. Due to the wide usage of digital devices, Machine Learning has offered a revolutionary way of solving tasks which can be data analysis, classification, forecasting, image recognition, etc.


Which machine learning algorithm should I use?

#artificialintelligence

A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is "which algorithm should I use?" Even an experienced data scientist cannot tell which algorithm will perform the best before trying different algorithms. We are not advocating a one and done approach, but we do hope to provide some guidance on which algorithms to try first depending on some clear factors. Click on the picture below to zoom in. To read more, click here.


Which machine learning algorithm should I use?

#artificialintelligence

A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is "which algorithm should I use?" Even an experienced data scientist cannot tell which algorithm will perform the best before trying different algorithms. We are not advocating a one and done approach, but we do hope to provide some guidance on which algorithms to try first depending on some clear factors.


Machine Learning (11) - Machine Learning Algorithms: Explained!

#artificialintelligence

One question that always pops up in any machine learning problem: Which algorithm should I use? What do the algorithms do anyways? After briefly going over a typical machine learning process, we have a closer look at third step, i.e. building the model: What algorithms are out there? Which one should we use? One of Microsoft's Data Scientist, Brandon Rohrer, has written a nice three-part blog series on introducing data science with no jargon: Furthermore, there is one really neat cheat sheet created by Microsoft's Data Science team on when to use which algorithm: Finally, one last resource that I hihgly recommend: Top 10 data mining algorithms in plain English.


Book: Machine Learning Algorithms From Scratch

#artificialintelligence

You must understand algorithms to get good at machine learning. The problem is that they are only ever explained using Math. In this mega Ebook written in the friendly Machine Learning Mastery style that you're used to, finally cut through the math and learn exactly how machine learning algorithms work. Using clear explanations, simple pure Python code (no libraries!) and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement a suite of linear, nonlinear and ensemble machine learning algorithms from scratch. I live in Australia with my wife and son and love to write and code.