Machine Learning Basics: A Comprehensive Introduction for Beginners

Key focus: machine learning, introduction, basics, beginners, algorithms, applications, concepts Introduction Machine learning has emerged as a groundbreaking technology that is transforming industries and reshaping our interaction with technology. From personalized recommendations to autonomous vehicles, machine learning algorithms play a pivotal role in these advancements. If you’re new to the field, this comprehensive beginner’s guide … Read more

Implementing Markov Chain in Python

Keywords: Markov Chain, Python, probability, data analysis, data science Markov Chain Markov chain is a probabilistic models that describe a sequence of observations whose occurrence are statistically dependent only on the previous ones. This article is about implementing Markov chain in Python Markov chain is described in one of the earlier posts. For better understanding … Read more

The Most Important Topics to Learn in Machine Learning

Keywords: machine learning, topics, probability, statistics, linear algebra, data preprocessing, supervised learning, unsupervised learning, deep learning, reinforcement learning, model evaluation, cross-validation, hyperparameter tuning. Why the buzz ? Machine learning has been generating a lot of buzz in recent years due to its ability to automate tasks that were previously thought to be impossible or required … Read more

Hidden Markov Models (HMM) – Simplified !!!

Markov chains are useful in computing the probability of events that are observable. However, in many real world applications, the events that we are interested in are usually hidden, that is we don’t observe them directly. These hidden events need to be inferred. For example, given a sentence in a natural language we only observe the … Read more

Markov Chains – Simplified !!

Key focus: Markov chains are a probabilistic models that describe a sequence of observations whose occurrence are statistically dependent only on the previous ones. ● Time-series data like speech, stock price movements.● Words in a sentence.● Base pairs on the rung of a DNA ladder. States and transitions Assume that we want to model the … Read more

Linear regression using python – demystified

Key focus: Let’s demonstrate basics of univariate linear regression using Python SciPy functions. Train the model and use it for predictions. Linear regression model Regression is a framework for fitting models to data. At a fundamental level, a linear regression model assumes linear relationship between input variables () and the output variable (). The input … Read more

Generating simulated dataset for regression problems

Key focus: Generating simulated dataset for regression problems using sklearn make_regression function (Python 3) is discussed in this article. Problem statement Suppose, a survey is conducted among the employees of a company. In that survey, the salary and the years of experience of the employees are collected. The aim of this data collection is to … Read more

Introduction to Signal Processing for Machine Learning

Key focus: Fundamentals of signal processing for machine learning. Speaker identification is taken as an example for introducing supervised learning concepts. Signal Processing A signal, mathematically a function, is a mechanism for conveying information. Audio, image, electrocardiograph (ECG) signal, radar signals, stock price movements, electrical current/voltages etc.., are some of the examples. Signal processing is … Read more