A beginner's introduction to the Top 10 Machine Learning (ML) algorithms, complete with figures and examples for easy understanding.
Source: Kdnugget
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For a myriad of data scientists, linear regression is the starting point of many statistical modeling and predictive analysis projects. The importance of fitting, both accurately and quickly, a linear model to a large data set cannot be overstated.
Source: TDS17454
I started my way in the Data Science world a few years back. I was a Software Engineer back then and I started to learn online first (before starting my Master's degree).
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Logistic Algorithms as the name suggest it comes under regression algorithms but with logistics regression the answer which comes is categorical as in the answer is either yes or no, either true or false so it is classified the values of fixed values are categorical the dependent variable the output, this is what we getting like this answers this will also categorize under the classification algorithms.
Source: HOB16845
Once the Business Intelligence reports and dashboards have been prepared and insights which are extracted from them, this information becomes the basis for predicting future values. And the accuracy of these predictions lies in the methods used.
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While there are many resources available online providing courses for TensorFlow picking a right one is always a difficult and confusing task for learners. To free you on that part, I have come here with the best online resources on TensorFlow that I have personally found useful.
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Many of us do not know that there is a proper list of machine learning algorithms. So here in this article, we will see some methods of using these algorithms.
Source: HOB38547
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