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1
Introduction To Machine Learning ll Machine Learning Course Explained With RealLife Examples (Hindi)
2
Classic Machine And Adaptive Machine ll Machine Learning Course Explained in Hindi
3
Basics Of Training And Testing Phase ll Machine Learning Course Explained in Hindi
4
Overfitting and Underfitting Explained with Examples in Hindi ll Machine Learning Course
5
Feature Selection Techniques Explained with Examples in Hindi ll Machine Learning Course
6
MultiClass Classification Approaches ll One Vs All and One Vs One Classification Explained in Hindi
7
Basics Of Principal Component Analysis Explained in Hindi ll Machine Learning Course
8
Principal Component Analysis(PCA) Part-2 Explained with Solved Example in Hindi l Machine Learning
9
Principal Component Analysis Part-3 Explained with Solved Explained in Hindi l Machine Learning
10
Regression Analysis l Dependent And Independent Variables (HINDI)
11
Linear Regression And Logistic Regression Explained in HINDI
12
Confusion Matrix ll Accuracy,Error Rate,Precision,Recall Explained with Solved Example in Hindi
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Curse Of Dimensionality Explained with Examples in Hindi ll Machine Learning Course
14
Managing Missing Features Explained with Examples in Hindi ll Machine Learning Course
15
Managing Categorial Data Explained with Examples in Hindi ll Machine Learning Course
16
Linear Regression Explained in Hindi ll Machine Learning Course
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Logistic Regression Explained in Hindi
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Polynomial Regression Explained in Hindi ll Machine Learning Course
19
Ridge Regression Explained in Hindi ll Machine Learning Course
20
Lasso Regression Explained in Hindi ll Machine Learning Course
21
Elastic Net Regression Explained in Hindi ll Machine Learning Course
22
Conditional Probability Explained with Solved Example and Sample Space in Hindi
23
Bayes Theorem Explained with Solved Example in Hindi ll Machine Learning Course
24
Naive Bayes Classifier ll Data Mining And Warehousing Explained with Solved Example in Hindi
25
Back Propagation Algorithm /Back Propagation Of Error (Part-1)Explained With Solved Example in Hindi
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Back Propagation Algorithm (Part-2) Explained with Solved Example in Hindi
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Back Propagation Algorithm (Part-3) Explained With Solved Example in Hindi
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Back Propagation Algorithm (Part-4) Explained with Solved Example in Hindi
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Naive Bayes Variants : Bernoulli Naive Bayes l Bernoulli Distribution Explained in Hindi
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Naive Bayes Variants : Multinomial Naive Bayes l Multinomial Distribution Explained in Hindi
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Naive Bayes Variants : Gaussian Naive Bayes Explained in Hindi
32
Support Vector Machine (SVM) Part-1 ll Machine Learning Course Explained in Hindi
33
Support Vector Machine (SVM) Part-2 ll Machine Learning Course Explained in Hindi
34
Non-Linear Support Vector Machine (SVM) And Kernel Function ll Machine Learning Course in Hindi
35
Decision Tree Algorithm Part-1 Explained With Example ll DMW ll ML Easiest Explanation Ever in Hindi
36
Decision Tree Algorithm Part-2 ll Constructing of Decision Tree ll ML ll DMW Explained in Hindi
37
Ensemble Learning l Machine Learning Course Easiest Explanation Ever in Hindi
38
Ensemble Method : Bagging (Bootstrap Aggregation) l Machine Learning Course in Hindi
39
Ensemble Method : Boosting ll Machine Learning Course Explained in Hindi
40
Voting Classifier : Hard Voting and Soft Voting Explained with Examples in Hindi ll Machine Learning
41
Random Forest Step-Wise Explanation ll Machine Learning Course Explained in Hindi
42
DBSCAN (Density Based Spatial Clustering Of Applications with Noise) ll Machine Learning (Hindi)
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K means Clustering Algorithm Explained With an Example Easiest And Quickest Way Ever In Hindi
44
Hierarchical Clustering : Agglomerative Clustering and Divisive Clustering Explained in Hindi
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Agglomerative Clustering (Single Linkage) Part-1 Explained with Solved Example in Hindi
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Agglomerative Clustering (Single Linkage) Part-2 Explained with Solved Example in Hindi
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Agglomerative Clustering (Complete Linkage) Explained with Solved Example in Hindi
48
Recommendation System : Content Based Recommendation and Collaborative Filtering Explained in Hindi
49
Data in Machine Learning Explained in Hindi
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How Much Data Do I Need in Machine learning Explained in Hindi
51
Bias and Variance Explained in Hindi l Machine Learning Course
52
Bias-Variance Trade-Off Explained in Hindi l Machine Learning Course
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Linear Regression Solved Numerical Part-1 Explained in Hindi l Machine Learning Course
54
Linear Regression Solved Numerical Part-2 Explained in Hindi l Machine Learning Course
55
Recurrent Neural Network (RNN) Part-1 Explained in Hindi
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Recurrent Neural Network (RNN) Part-2 Explained in Hindi
57
Loading Data Using Pandas Explained in Hindi l Machine Learning Course
58
Understanding Data Using Statistics Explained in Hindi l Machine Learning Course
59
Visualization of Data Using Matplotlib Part-1 Explained in Hindi l Machine Learning Course
60
Visualization of Data Using Matplotlib Part-2 Explained in Hindi l Machine Learning Course
61
Data Preprocessing Techniques : Normalization Explained with Python in Hindi l Machine Learning
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Data Preprocessing Techniques : Standardization Explained with Python in Hindi l Machine Learning
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Data Preprocessing Techniques : Binarization Explained with Python in Hindi l Machine Learning
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Training and Testing data Explained in Hindi with Python in Hindi l Machine Learning Course
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Linear Regression Single Variable Explained with Python in Hindi l Machine Learning Course
66
Linear Regression Multiple Variables Explained with Python in Hindi l Machine Learning Course
67
Logistic Regression Explained with Python in Hindi l Machine Learning Course
68
K Means Clustering Implementation with Python Part-1 Explained in Hindi l Machine Learning Course
69
K Means Clustering Implementation with Python Part-2 Explained in Hindi l Machine Learning Course
Description:
Embark on a comprehensive 10-hour machine learning course taught in Hindi, covering fundamental concepts to advanced techniques. Learn about classic and adaptive machines, training and testing phases, overfitting and underfitting, feature selection, and multiclass classification approaches. Explore principal component analysis, regression analysis, confusion matrices, and the curse of dimensionality. Dive into various regression techniques, including linear, logistic, polynomial, ridge, lasso, and elastic net. Understand probability concepts, Bayes theorem, and different Naive Bayes classifiers. Master neural networks with back propagation algorithm explanations. Study support vector machines, decision trees, ensemble learning methods, and clustering algorithms. Discover recommendation systems, data preprocessing techniques, and practical implementations using Python and popular libraries like Pandas, Matplotlib, and scikit-learn.

Machine Learning

5 Minutes Engineering
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#Computer Science #Machine Learning #Data Science #Data Visualization #Ensemble Learning #Mathematics #Statistics & Probability #Statistical Modeling #Regression Analysis #Classification #Feature Selection #Naive Bayes #Principal Component Analysis
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Introduction To Machine Learning ll Machine Learning Course Explained With RealLife Examples (Hindi)