Machine Learning

Application of differentiations in neural networks

Differential calculus is an important tool in machine learning algorithms. Neural networks in particular, the gradient descent algorithm depends on the gradient, which is a quantity computed by differentiation. In this tutorial, we will see how the back-propagation technique is used in finding the gradients in neural networks. After completing this tutorial, you will know What is a total differential and total derivative How to compute the total derivatives in neural networks How back-propagation helped in computing the total derivatives […]

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Machine Learning

Method of Lagrange Multipliers: The Theory Behind Support Vector Machines (Part 2: The Non-Separable Case)

This tutorial is an extension of Method Of Lagrange Multipliers: The Theory Behind Support Vector Machines (Part 1: The Separable Case)) and explains the non-separable case. In real life problems positive and negative training examples may not be completely separable by a linear decision boundary. This tutorial explains how a soft margin can be built that tolerates a certain amount of errors. In this tutorial, we’ll cover the basics of a linear SVM. We won’t go into details of non-linear […]

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Machine Learning

Method of Lagrange Multipliers: The Theory Behind Support Vector Machines (Part 3: Implementing An SVM From Scratch In Python)

The mathematics that powers a support vector machine (SVM) classifier is beautiful. It is important to not only learn the basic model of an SVM but also know how you can implement the entire model from scratch. This is a continuation of our series of tutorials on SVMs. In part1 and part2 of this series we discussed the mathematical model behind a linear SVM. In this tutorial, we’ll show how you can build an SVM linear classifier using the optimization routines […]

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Machine Learning

Some Language Features in Python

The Python language syntax is quite powerful and expressive. Hence it is concise to express an algorithm in Python. Maybe this is the reason why it is popular in machine learning, as we need to experiment a lot in developing a machine learning model. If you’re new to Python but with experience in another programming language, you will sometimes find Python syntax understandable but weird. If you are used to writing in C++ or Java and then transitioning to Python, […]

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Machine Learning

Python Classes and Their Use in Keras

Classes are one of the fundamental building blocks of the Python language, which may be applied in the development of machine learning applications. As we shall see, the Python syntax for developing classes is simple and can be applied to implement callbacks in Keras.  In this tutorial, you will discover the Python classes and their functionality.  After completing this tutorial, you will know: Why Python classes are important How to define and instantiate a class and set its attributes  How […]

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Machine Learning

Understanding Traceback in Python

When an exception occurs in a Python program, often a traceback will be printed. Knowing how to read the traceback can help you easily identify the error and make a fix. In this tutorial, we are going to see what the traceback can tell you. After completing this tutorial, you will know: How to read a traceback How to print the call stack without an exception What is not shown in the traceback Kick-start your project with my new book […]

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Machine Learning

Running and Passing Information to a Python Script

Running your Python scripts is an important step in the development process because it is in this manner that you’ll get to find out if your code works as you intended it to. Also, it is often the case that we would need to pass information to the Python script for it to function. In this tutorial, you will discover various ways of running and passing information to a Python script. After completing this tutorial, you will know: How to […]

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Machine Learning

Anomaly Detection with Isolation Forest and Kernel Density Estimation

Anomaly detection is to find data points that deviate from the norm. In other words, those are the points that do not follow expected patterns. Outliers and exceptions are terms used to describe unusual data. Anomaly detection is important in a variety of fields because it gives valuable and actionable insights. An abnormality in an MR imaging scan, for instance, might indicate tumorous region in the brain, while an anomalous readout from a manufacturing plant sensor could indicate a broken […]

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Machine Learning

Python Debugging Tools

In all programming exercises, it is difficult to go far and deep without a handy debugger. The built-in debugger, pdb, in Python is a mature and capable one that can help us a lot if you know how to use it. In this tutorial, we are going to see what the pdb can do for you as well as some of its alternatives. In this tutorial, you will learn: What a debugger can do How to control a debugger The […]

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Machine Learning

More Special Features in Python

Python is an awesome programming language! It is one of the most popular languages for developing AI and machine learning applications. With a very easy-to-learn syntax, Python has some special features that distinguish it from other languages. In this tutorial, we’ll talk about some unique attributes of the Python programming language. After completing this tutorial, you will know: Constructs for list and dictionary comprehension How to use the zip and enumerate functions What are function contexts and decorators What is […]

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