Machine Learning # 2 Classification & Data Preprocessing
In machine learning, classification solve the problem of predicting the categories of a given data point. Pre-processing refers to the transformations applied to our data before feeding it to the algorithm. 1 like = 1 AI
********************************************************************
Vocabulary:
📗Binarization is used when we want to convert our numerical value into Boolean values (true / false).
📗Mean removal mean is a common preprocessing technique used in machine learning. It is usually useful to remove the mean of our feature vector so that each feature is centered on zero. We do this in other to remove bias from the features in our feature vector.
📗Scaling: In our feature vector, the value of each feature vector can varied around many random value. So it become important to scale those features so that it is a level playing field for the machine learning algorithm to train on. We don’t want any feature to be artificially large or small because of the nature of measurement.
📗Normalization: We use the process of normalization to modify the value in the feature vector so that we can measure them on a common scale. In machine learning, we use many different forms of normalization. Some of the most common forms of normalization aim to modify the values so that they sum up to one.
********************************************************************
🔗Links:
How to Install Atom: http://tiny.cc/be6i3y
Download Atom: https://atom.io/
Code Source: https://github.com/soulstartlight/Mac...
#MachineLearning #EPICSOCIETY
On this page of the site you can watch the video online Machine Learning # 2 Classification & Data Preprocessing with a duration of hours minute second in good quality, which was uploaded by the user SoulSociety 24 February 2019, share the link with friends and acquaintances, this video has already been watched 2,234 times on youtube and it was liked by 12 viewers. Enjoy your viewing!
