Prerequisite Python3 PyCharm or any other python IDE Homebrew cmake (brew install cmake) dlib (pip3 install dlib) The steps in bracket are specific to mac. Code https://gist.github.com/rohitsingh20122992/0c8fa7478dedc35436bebd2c13b096da The algorithm behind will be covered in subsequent tutorial. Test Input Test Output Reference: Linked In Course On Face Recognition If you liked this article and would like... Continue Reading →
A tutorial for MNIST – Digit Recognition Using scikit learn
Introduction This is again a note to myself. This code has been prepared following different tutorials and SO answers. I have tried to cover many of them in reference below. The notebook is commented to the best of my ability. Starting with 11% in first trial, the final model is able to achieve accuracy of... Continue Reading →
How do Machines Learn : Hoeffding’s Inequality, in sample and out of sample using Game of Throne Analogy
The war is almost here and people of Winterfell have to decide whom they wish to declare the king in the North. There are one million citizen in Winterfell. These one million citizens need to choose between Daenerys Targaryen and Jon Snow. But there is one man who wish to know the results before hand... Continue Reading →
Introduction to Machine Learning Terminology and Perceptron
We talked about introduction to machine learning here. Let's say, we have two armies: red and blue. The black line is the border separating these two armies. The line is curved and it is drawn using visual inspection. But the kings are mad and they demand a straight line, not a curved one. To please... Continue Reading →
An Introduction To Machine Learning
Machine Learning is a kind of buzz words these days; sort of a mysterious new guy in the class whom everyone wants to be friend with. On the onset, I would like to think Machine Learning as a part of tool kit of every Software Engineer. And conceptually it's not different from the Mathematics, Algorithm,... Continue Reading →
A tutorial To Find Best Scikit classifiers For Sentiment Analysis
An introduction to sentiment analysis comparing different classifiers using scikit, nltk and panda.
A Tutorial to Understand Decision Tree ID3 Learning Algorithm
Introduction Decision Tree learning is used to approximate discrete valued target functions, in which the learned function is approximated by Decision Tree. To imagine, think of decision tree as if or else rules where each if-else condition leads to certain answer at the end. You might have seen many online games which asks several question and lead... Continue Reading →
Entropy In Machine Learning
Entropy is a measure of randomness. In other words, its a measure of unpredictability. Let's take an example of a coin toss. Suppose we tossed a coin 4 times, and the output of the events came as {Head, Tail, Tail, Head}. Based solely on this observation, if you have to guess what will be the... Continue Reading →
A Beginner Tutorial For ML Decision Tree Model Using Scikit And Panda
Prerequisite Python, Scikit and Panda installed in your laptop. It's better to install conda as it has all the required libraries. Install Jupyter too. It really helps in python coding. Panda Panda is a popular python library to explore and manipulate data. Scikit Scikit is popular machine learning framework in python. Regression Regression is process to... Continue Reading →
Example : Use Scikit-Learn, PySpark ML Models in Java Using MLeap
Introduction: Many of the most popular machine learning frameworks are based in python. The other fact is that java has been around for quite some time as preferred language for backend development. One way could be to expose ml models as APIs. Downside being need to manage another service and extra calls over network which... Continue Reading →