Deep Dive into Machine Learning
Learn about each technique or algorithm used in the Machine Learning domain for building models, solving real-world problems, and delving into one of the most exciting technological domains in the twenty-first century.
Supervised Learning
Learn about Supervised Learning, one of the most widely used Machine Learning techniques. This technique requires trained data and input-output pairs, so are familiar with all aspects and master the technique.
Linear Regression
Learn about Linear Regression, a simple yet powerful algorithm for determining variable relationships. It should be noted that Linear Regression is li
Locally Weighted Regression
Learn about Locally Weighted Regression, which differs from Linear Regression in its non parametric approach. Learn about the mathematics that is invo
Logistic Regression
Understand Logistic Regression with its mathematical concepts, such as the Lost Function and decision surfacing.
K-Nearest Neighbors (KNN)
Learn about K Nearest Neighbor, a popular non-parametric Machine Learning algorithm with applications.
Naive Bayes
Understand the concept of Naive Bayes classification, as well as its implementation, types, and real-world applications.
Decision Trees
Learn about decision trees, which are an important component of machine learning and prediction algorithms. Flowchart-like structures with nodes and l
Random Forest
Random Forest methods were a huge breakthrough in regression and classification difficulties. For complex machine learning issues, a combination of de
Support Vector Machine (SVM)
Support Vector Machines are supervised machine learning algorithms that are particularly efficient for large numbers of samples. Learn how to put it i
Boosting Algorithm
A critical supervised learning algorithm that, as the name implies, boosts the accuracy and overall performance of the models by reducing variance and
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Introduction to Supervised Learning
By Pratyksh
● Published At Nov 2021
This article explores the ins and outs of Supervised Learning.... Keep reading ..
Classification vs Regression
By Arun Nawani
● Published At Nov 2021
In this blog, we’ll learn about fundamental differences between classification and regression tasks. ... Keep reading ..
Drawbacks of Supervised Learning
By Akshat Chaturvedi
● Published At May 2022
In this blog, we’ll discuss the drawbacks of the supervised machine learning technique.... Keep reading ..
Unsupervised Learning
This is in contrast to Supervised Learning, which does not use trained data but has a long list of real-world applications and is widely used by many tech companies.
Clustering
Clustering is a prominent unsupervised learning approach. It allows users to classify and group certain data points, resulting in more distinct and ac
Evaluating Classification Models Performance
Creating and deploying models isn't the only job of a data scientist or machine learning engineer. It is also necessary to analyse the performance of
Unsupervised Learning
By Arun Nawani
● Published At Nov 2021
This article gives you a good insight into Unsupervised machine learning techniques, the perfect starting point for beginners in the field. ... Keep reading ..
Reinforcement Learning
Another machine learning technique that aids in achieving a better and more accurate output is reinforcement learning. This strategy improves a model's decision-making and decision-making path.
Introduction to Reinforcement Learning
By Pratyksh
● Published At Nov 2021
This article is an overview of Reinforcement learning.... Keep reading ..
The Bellman Equation
By Tushar Tangri
● Published At Dec 2021
The Bellman Equation has a broader application in solving problems of reinforcement learning. It helps machines learn using rewards as favorable reinforcement. ... Keep reading ..
Markov Decision Process
By Anant Dhakad
● Published At Nov 2021
In this blog, we will learn about the Markov Decision Process. ... Keep reading ..
Q-Learning
By Tashmit
● Published At Feb 2022
The primary objective of this article is to understand Q-learning.... Keep reading ..
Epsilon Greedy Algorithm
By Tashmit
● Published At Dec 2021
This article aims to throw some light on the epsilon greedy algorithm.... Keep reading ..
What is Genetic Algorithm?
By Akshat Chaturvedi
● Published At Jan 2022
In this blog, we’ll learn what Genetic Algorithm is and how real-life evolution theories inspire it.... Keep reading ..
TradeOffs like Exploration vs. Exploitation
By Tashmit
● Published At Mar 2022
This blog aims to understand tradeoffs like exploration and exploitation.... Keep reading ..
Real-life Applications of Reinforcement Learning
By Arun Nawani
● Published At Jan 2022
This blog walks you through on real-life applications of RL agents to give you an insight into just how powerful it is.... Keep reading ..
Drawbacks of Unsupervised Learning
By Prakriti
● Published At May 2022
This article will take you through Unsupervised Learning and its drawbacks.... Keep reading ..
Important Differences
Machine learning has many subcategories and techniques, each with some similarities and differences. It is critical to understand how these algorithms differ in order to make better decisions when dealing with classification or regression problems. One of the most significant distinctions is between supervised and unsupervised learning, technique, application, limitations, and data.
Linear vs. Non-Linear Classification
By Shabeg Singh Gill
● Published At Jan 2022
In this blog post, we'll learn about Linear Classification and Non-Linear Classification and then compare and contrast the two. ... Keep reading ..
Applications of Machine Learning
Discover how Machine Learning and its algorithms are used to solve real-world problems. Machine Learning has enabled everything from weather prediction to recommendation systems to self-driving cars.
Recommendation System - Amazon - Application of ML
By Mayank Goyal
● Published At Feb 2022
This article will discuss the recommendation system and how amazon is currently using it. At last, we will see a basic implementation on the amazon dataset.... Keep reading ..
Self-Driving Cars - Application of ML
By Mandla Dharani
● Published At Dec 2021
In this blog, we discussed self-driving cars followed by reinforcement learning and algorithms required at last we learned some hardware components. ... Keep reading ..
Weather Forecasting - Application of ML
By soham Medewar
● Published At Dec 2021
This blog will explain how Machine Learning helps in weather forecasting. In the implementation part, I will be implementing the small model, which shows the algorithms required for weather forecasting. ... Keep reading ..
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