← Free Learning Library

Machine Learning

Machine Learning with Python for Beginners (Hindi)

A beginner-friendly Hindi video series that walks through core machine learning concepts and Python implementations, from features and labels to regression, classification, and model evaluation.

Learn from: the original creator. Original content published on YouTube. DigitalSkillX organizes these public resources into a structured learning path. DigitalSkillX does not claim ownership or partnership.

Lessons
23
Time
About 9 hr 46 min
Level
beginner

Now playing: [Hindi] Installing Python Scikit learn For ML - Machine Learning Tutorials Using Python In Hindi

About this path

This learning path is built from CodeWithHarry's Hindi machine learning playlist. It starts with the motivation for learning ML and the basic vocabulary of features and labels, then moves into data collection, supervised vs unsupervised learning, and setting up scikit-learn. The middle covers linear regression in depth, including the derivation, Python code, loss functions, and gradient descent variants. Later lessons introduce classification with K Nearest Neighbors, overfitting and underfitting, logistic regression, and evaluation metrics like precision, recall, confusion matrix, and F1 score. Two project videos give you a chance to apply what you have learned. The series is taught in Hindi and uses Python throughout.

What you will learn

  • Explain what machine learning is and why it is useful
  • Identify features and labels in a dataset
  • Collect and prepare data for ML tasks
  • Distinguish between supervised and unsupervised learning
  • Install and use scikit-learn in Python
  • Split data into training and test sets
  • Build and interpret simple and multiple linear regression models
  • Understand loss functions and gradient descent, including mini-batch and stochastic variants
  • Apply K Nearest Neighbors for classification
  • Recognize overfitting and underfitting

Who this is for

Beginners who want a structured free introduction before deeper practice.

Curriculum

Section 1: Getting Started with Machine Learning

  1. Lesson 1: [Hindi] Why Learn Machine Learning? - Machine Learning Tutorials Using Python In Hindi

    This opening video explains why machine learning is worth learning and gives a broad overview of the field. It sets expectations for the series and introduces the Python-based approach used throughout.

    Open on YouTube
  2. Lesson 2: [Hindi] Some Machine Learning Facts & Motivation - Machine Learning Tutorials Using Python In Hindi

    The video shares interesting facts about machine learning and offers motivation for beginners. It helps build context for why ML skills are in demand.

    Open on YouTube
  3. Lesson 3: [Hindi] What Are Features And Labels In ML? - Machine Learning Tutorials Using Python In Hindi

    This lesson defines features and labels, two fundamental terms in machine learning. It shows how they appear in datasets and why distinguishing them matters for building models.

    Open on YouTube
  4. Lesson 4: [Hindi] Data Collection For Machine Learning? - Machine Learning Tutorials Using Python In Hindi

    The video covers how data is collected for machine learning projects. It discusses sources of data and considerations before you start building a model.

    Open on YouTube
  5. Lesson 5: [Hindi] Supervised And Unsupervised Learning! - Machine Learning Tutorials Using Python In Hindi

    This lesson explains the difference between supervised and unsupervised learning. It gives examples of each type and when to use them.

    Open on YouTube

Section 2: Setting Up and Preparing Data

  1. Lesson 6: [Hindi] Installing Python Scikit learn For ML - Machine Learning Tutorials Using Python In Hindi

    A step-by-step guide to installing scikit-learn, a popular Python library for machine learning. It covers the setup needed to follow along with the coding lessons.

    Open on YouTube
  2. Lesson 7: [Hindi] Training And Test Data In ML - Machine Learning Tutorials Using Python In Hindi

    This video explains why data is split into training and test sets. It shows how to perform the split in Python and why it helps evaluate model performance honestly.

    Open on YouTube

Section 3: Linear Regression

  1. Lesson 8: [Hindi] Simple Linear Regression Explained! - Machine Learning Tutorials Using Python In Hindi

    An introduction to simple linear regression, covering the concept and how it models a relationship between one input and one output. The video explains the intuition behind the line of best fit.

    Open on YouTube
  2. Lesson 9: [Hindi] Multiple Regression Model Explained! - Machine Learning Tutorials Using Python In Hindi

    This lesson extends linear regression to multiple input variables. It explains how multiple regression works and why it is useful when more than one feature affects the outcome.

    Open on YouTube
  3. Lesson 10: [Hindi] Linear Regression Code In Python Sklearn! - Machine Learning Tutorials In Hindi

    A hands-on coding session where linear regression is implemented in Python using scikit-learn. It walks through loading data, fitting the model, and making predictions.

    Open on YouTube
  4. Lesson 11: [Hindi] How Does Linear Regression Model Work? (Derivation) - Machine Learning Tutorials In Hindi

    This video dives into the mathematics behind linear regression. It derives the formulas used to find the best-fitting line, helping you understand what happens under the hood.

    Open on YouTube
  5. Lesson 12: [Hindi] Loss Functions and Gradient Descent - Machine Learning Tutorials Using Python In Hindi

    The lesson introduces loss functions and gradient descent, two key ideas for training models. It explains how loss measures error and how gradient descent minimizes it.

    Open on YouTube
  6. Lesson 13: [Hindi] Mini Batch and Stochastic Gradient Descent -Machine Learning Tutorials Using Python In Hindi

    This video covers mini-batch and stochastic gradient descent, variations that update parameters more frequently. It compares them to batch gradient descent and discusses trade-offs.

    Open on YouTube

Section 4: Classification and Model Fit

  1. Lesson 14: [Hindi] Supervised Learning : Classification - Machine Learning Tutorials Using Python In Hindi

    An introduction to classification, a type of supervised learning where the output is a category. It explains the basic idea and gives examples of classification problems.

    Open on YouTube
  2. Lesson 15: [Hindi] K Nearest Neighbor Classification In Python - Machine Learning Tutorials Using Python Hindi

    This lesson shows how to implement K Nearest Neighbors classification in Python. It covers the basic steps of training and predicting with KNN.

    Open on YouTube
  3. Lesson 16: K Nearest Neighbors: Pros, Cons and Working - Machine Learning Tutorials Using Python In Hindi

    The video explains how K Nearest Neighbors works in detail and discusses its pros and cons. It helps you decide when KNN is a good choice.

    Open on YouTube
  4. Lesson 17: OverFitting And UnderFitting In Models Explained - Machine Learning Tutorials Using Python In Hindi

    This lesson explains overfitting and underfitting, two common problems in model training. It describes how to spot them and what they mean for model performance.

    Open on YouTube
  5. Lesson 18: Logistic Regression : Overview And Working - Machine Learning Tutorials Using Python In Hindi

    An overview of logistic regression, a classification algorithm. The video explains how it works and why it is used for binary classification tasks.

    Open on YouTube
  6. Lesson 19: Coding Logistic Regression In Python | Machine Learning Tutorials Using Python In Hindi

    A coding session where logistic regression is implemented in Python. It walks through the steps of building, training, and evaluating a logistic regression model.

    Open on YouTube

Section 5: Projects and Evaluation

  1. Lesson 20: Project 1: End To End Python ML Project (Complete)| Machine Learning Tutorials Using Python In Hindi

    A complete end-to-end machine learning project in Python. It ties together the concepts and steps covered earlier, from data preparation to model evaluation.

    Open on YouTube
  2. Lesson 21: Handwritten Digit Recognition on MNIST dataset | Machine Learning Tutorials Using Python In Hindi

    This project builds a handwritten digit recognizer using the MNIST dataset. It demonstrates image classification with a real dataset.

    Open on YouTube
  3. Lesson 22: Precision, Recall, Confusion matrix & F1-Score | Machine Learning Tutorials Using Python In Hindi

    The video explains precision, recall, confusion matrix, and F1 score. These metrics help you evaluate classification models beyond simple accuracy.

    Open on YouTube
  4. Lesson 23: Evaluating Classifiers in Python: Precision, Recall & F1 Score | Machine Learning Tutorials In Hindi

    A practical lesson on computing precision, recall, and F1 score in Python. It shows how to use scikit-learn to evaluate classifiers with these metrics.

    Open on YouTube

Your progress

0 of 23 lessons completed (0%).

Complete this learning path to become eligible for your DigitalSkillX certificate.

Related learning