Statistics for Machine Learning

Statistics for M.L and D.S Vol-2: In this article, we are going to discuss some more about statistical concepts which are applied for Machine Learning(M.L) and Data Science(D.S). In the last article, we talked about some basic concepts like measures of central tendency, Inter-Quartile range, Data Matrix, Cases and Variables, some shapes of distributions. Now, we are going to cover some more concepts like Z-Score, Standard Deviation, Variance, Correlation, Regression. As i told you before, this all terminologies will help you to understand what is Data Science and Machine learning. So without wasting any time, let's move forward. ***Important note->  My coding or say python environment is the jupyter notebook, you are free to use any other environment but I'll always prefer jupyter over others. Here's the link of the first article: Statistics for M.L and D.S Vol-1 Standard Deviation and Variance: As we have seen in the last article, two measures of Variabili

Basic statistics for M.L and D.S VOL1: In this Blog, i am going to talk about the statistical concepts used in Machine Learning. Data science and Machine learning is the hottest career path in the 21st century, but also it's a central skill. But become a data scientist neither easy nor difficult task. You must have a keen knowledge of mathematics, have a hands-on experience on programming(mostly in R and Python), must have known theoretical concepts used for M.L(Machine Learning). Here, i am going to familiarize you with some statistical concepts used to become an M.L engineer or Data Scientist. This is the first part of the whole blog. It would contain more than 2 articles in order to cover the concepts of mathematics used in D.S(Data Science) and M.L. These will also include some probability distribution concepts. So without wasting any time, let's move on.  Exploring Data: Cases and variables and levels of measurement: Imagine you are very much interested in