Beginner Lessons

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Cracking Statistics Interview Questions

Cracking String Methods Interview Questions

Cracking Data Filteration Interview Questions

A Step-by-Step Guide to Solving ML Interview Questions on Leetcode

Cracking ML Interviews in Product-Based Companies: Top 25 Interview Questions Discussion

Log Normalization for Outliers: Convert Skewed Data to Normal Distribution

Hands-On: Implementation Of Gradient Boosting Algorithm

Gradient Boosting Regression: Step-by-Step Implementation Guide

Understanding Gradient Boosting: The Math Behind Regression Problems

Motivation behind boosting algorithms

Master Boosting in Machine Learning

Decoding Gradient Boosting: The Math Behind Classification Problems

Master Stacking in Machine Learning

Master Bagging in Machine Learning

Outro Of Project: Cutomer segmentation

Model Pusher: Customer Segmentation

Model Evaluation: Customer Segmentation

Model Evaluation: Customer Segmentation

Exploratory Data Analysis: Customer segmentation

Intro Of Project - Customer Segmentation

Evaluation Metric: Silhouette Score

Optimization Of KNN: KD Tree and Ball Tree

Random Forests Optimization: Hyperparameter Tuning

Overfitting in DT: Pruning Techniques

Entropy & Information Gain

K-Means Clustering Algorithm

Decision Tree

Model Prediction and Evaluation

Exploratory Data Analysis: Outlier Detection and Normalization

Exploratory Data Analysis: Outlier Handling Techniques

Exploratory Data Analysis: Feature Selection and Data Imputation

Model Evaluation Metric: Confusion Matrix

Regularization Techniques

Understanding Bias and Variance

Model Evaluation

Exploratory Data Analysis

Model Evaluation Metric: R-square vs Adjusted R-square

Learning Rate Explained

Linear Regression and Gradient Descent

Future of Machine Learning

Challenges of Machine Learning

Types of Machine Learning: Supervised, Unsupervised, Reinforcement

History and Evolution of Machine Learning

Machine Learning Applications Across Industries

What is Machine Learning? | Lecture 1 | Free Video

Become a Data Scientist in just 90 days |

AI vs ML vs DL vs DS: What's the Difference?