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Lecture 5.1 : Sigmoid Function in 3D with Python Code
www.javatpoint.com/numpy-meshgrid
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zhlédnutí: 41

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Lecture 5: Sigmoid Neuron/ Need for Smoother Decision Boundary25:39Lecture 5: Sigmoid Neuron/ Need for Smoother Decision Boundary
Lecture 5: Sigmoid Neuron/ Need for Smoother Decision Boundary
zhlédnutí 45Před 21 dnem
Lecture 5: Sigmoid Neuron/ Need for Smoother Decision Boundary
Lecture 4: DL- Perceptron Drawbacks/ Need for Non-linear Activation Functions17:28Lecture 4: DL- Perceptron Drawbacks/ Need for Non-linear Activation Functions
Lecture 4: DL- Perceptron Drawbacks/ Need for Non-linear Activation Functions
zhlédnutí 65Před měsícem
towardsdatascience.com/how-neural-networks-solve-the-xor-problem-59763136bdd7
Lecture 1.1 : MP Neuron Python Hands-on, Loading and Visualizing the dataset | Train-test Split16:12Lecture 1.1 : MP Neuron Python Hands-on, Loading and Visualizing the dataset | Train-test Split
Lecture 1.1 : MP Neuron Python Hands-on, Loading and Visualizing the dataset | Train-test Split
zhlédnutí 135Před 11 měsíci
Lecture 1.1 : MP Neuron Python Hands-on, Loading and Visualizing the dataset | Train-test Split
Lecture 1: Deep Generative Models | Introduction to Auto-encoders | Variational Auto-encoders13:08Lecture 1: Deep Generative Models | Introduction to Auto-encoders | Variational Auto-encoders
Lecture 1: Deep Generative Models | Introduction to Auto-encoders | Variational Auto-encoders
zhlédnutí 136Před rokem
Lecture 1: Deep Generative Models | Introduction to Auto-encoders | Variational Auto-encoders
Lecture 8: Solved Problems on Conditional Probability13:25Lecture 8: Solved Problems on Conditional Probability
Lecture 8: Solved Problems on Conditional Probability
zhlédnutí 138Před rokem
Lecture 8: Solved Problems on Conditional Probability
Lecture 7: An intuitive introduction to Conditional Probability13:38Lecture 7: An intuitive introduction to Conditional Probability
Lecture 7: An intuitive introduction to Conditional Probability
zhlédnutí 77Před rokem
Lecture 7: An intuitive introduction to Conditional Probability
Lecture 6: Permutations and Combinations17:30Lecture 6: Permutations and Combinations
Lecture 6: Permutations and Combinations
zhlédnutí 40Před rokem
Lecture 6: Permutations and Combinations
Lecture 5: Basic Principle of Counting | Permutations | Intuitive Explanation11:55Lecture 5: Basic Principle of Counting | Permutations | Intuitive Explanation
Lecture 5: Basic Principle of Counting | Permutations | Intuitive Explanation
zhlédnutí 32Před rokem
Lecture 5: Basic Principle of Counting | Permutations | Intuitive Explanation
Lecture 4: Frequency based Probability definition11:20Lecture 4: Frequency based Probability definition
Lecture 4: Frequency based Probability definition
zhlédnutí 69Před rokem
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Lecture 3: Axioms of Probability9:02Lecture 3: Axioms of Probability
Lecture 3: Axioms of Probability
zhlédnutí 29Před rokem
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Lecture 2 : Basics of Probability9:52Lecture 2 : Basics of Probability
Lecture 2 : Basics of Probability
zhlédnutí 37Před 2 lety
Connect with me : www.linkedin.com/in/parth-modi-5587a1148/
Introduction to Statistics (for Data Science)8:38Introduction to Statistics (for Data Science)
Introduction to Statistics (for Data Science)
zhlédnutí 50Před 2 lety
Connect with me : www.linkedin.com/in/parth-modi-5587a1148/
Lecture 3: Deep Learning with Python Hands-on: Perceptron Learning Algorithm Convergence9:41Lecture 3: Deep Learning with Python Hands-on: Perceptron Learning Algorithm Convergence
Lecture 3: Deep Learning with Python Hands-on: Perceptron Learning Algorithm Convergence
zhlédnutí 117Před 2 lety
Connect with me : www.linkedin.com/in/parth-modi-5587a1148/ Convergence Proof : www.cs.columbia.edu/~mcollins/courses/6998-2012/notes/perc.converge.pdf
Lecture 2 : Deep Learning with Python Hands-on: Perceptron Learning Algorithm14:00Lecture 2 : Deep Learning with Python Hands-on: Perceptron Learning Algorithm
Lecture 2 : Deep Learning with Python Hands-on: Perceptron Learning Algorithm
zhlédnutí 109Před 2 lety
Connect with me : www.linkedin.com/in/parth-modi-5587a1148/
Difference Between Scalar/Vector/Matrix/ and Tensors with Python Hands-on | Part 216:33Difference Between Scalar/Vector/Matrix/ and Tensors with Python Hands-on | Part 2
Difference Between Scalar/Vector/Matrix/ and Tensors with Python Hands-on | Part 2
zhlédnutí 208Před 2 lety
Difference Between Scalar/Vector/Matrix/ and Tensors with Python Hands-on | Part 2
But What is a Tensor? With Python hands on with TensorFlow | Part 127:22But What is a Tensor? With Python hands on with TensorFlow | Part 1
But What is a Tensor? With Python hands on with TensorFlow | Part 1
zhlédnutí 125Před 2 lety
But What is a Tensor? With Python hands on with TensorFlow | Part 1
Machine Learning Lecture 8.2 : Bias-Variance Trade-off in detail11:54Machine Learning Lecture 8.2 : Bias-Variance Trade-off in detail
Machine Learning Lecture 8.2 : Bias-Variance Trade-off in detail
zhlédnutí 107Před 2 lety
Machine Learning Lecture 8.2 : Bias-Variance Trade-off in detail
Machine Learning Lecture 8.1 : Ensemble Learning with python Code19:24Machine Learning Lecture 8.1 : Ensemble Learning with python Code
Machine Learning Lecture 8.1 : Ensemble Learning with python Code
zhlédnutí 211Před 2 lety
Machine Learning Lecture 8.1 : Ensemble Learning with python Code
Machine Learning Lecture 4.4 : Overfitting and Underfitting in Decision Trees8:03Machine Learning Lecture 4.4 : Overfitting and Underfitting in Decision Trees
Machine Learning Lecture 4.4 : Overfitting and Underfitting in Decision Trees
zhlédnutí 343Před 2 lety
Machine Learning Lecture 4.4 : Overfitting and Underfitting in Decision Trees
Machine Learning Lecture 4.5: Decision Tree Optimization by Pre-Pruning and Post-Pruning | with Code10:44Machine Learning Lecture 4.5: Decision Tree Optimization by Pre-Pruning and Post-Pruning | with Code
Machine Learning Lecture 4.5: Decision Tree Optimization by Pre-Pruning and Post-Pruning | with Code
zhlédnutí 2,4KPřed 2 lety
Machine Learning Lecture 4.5: Decision Tree Optimization by Pre-Pruning and Post-Pruning | with Code
Machine Learning Lecture 4.3 : Decision Tree Classifier based on Gini Impurity with Python Code20:49Machine Learning Lecture 4.3 : Decision Tree Classifier based on Gini Impurity with Python Code
Machine Learning Lecture 4.3 : Decision Tree Classifier based on Gini Impurity with Python Code
zhlédnutí 551Před 3 lety
Machine Learning Lecture 4.3 : Decision Tree Classifier based on Gini Impurity with Python Code
Python Practice : How to Print various patterns in Python11:54Python Practice : How to Print various patterns in Python
Python Practice : How to Print various patterns in Python
zhlédnutí 47Před 3 lety
Python Practice : How to Print various patterns in Python
Machine Learning Lecture 4.2 : Building a Decision Tree based on Information Gain/Entropy measure29:59Machine Learning Lecture 4.2 : Building a Decision Tree based on Information Gain/Entropy measure
Machine Learning Lecture 4.2 : Building a Decision Tree based on Information Gain/Entropy measure
zhlédnutí 109Před 3 lety
Machine Learning Lecture 4.2 : Building a Decision Tree based on Information Gain/Entropy measure
Machine Learning Lecture 1.6 : Naive Bayes Algorithm17:58Machine Learning Lecture 1.6 : Naive Bayes Algorithm
Machine Learning Lecture 1.6 : Naive Bayes Algorithm
zhlédnutí 150Před 3 lety
Machine Learning Lecture 1.6 : Naive Bayes Algorithm
Machine Learning Lecture 4.1 : Introduction to Decision Tree6:59Machine Learning Lecture 4.1 : Introduction to Decision Tree
Machine Learning Lecture 4.1 : Introduction to Decision Tree
zhlédnutí 70Před 3 lety
Machine Learning Lecture 4.1 : Introduction to Decision Tree
Machine Learning Lecture 3.2 : Soft Margin SVM Mathematical Derivation14:41Machine Learning Lecture 3.2 : Soft Margin SVM Mathematical Derivation
Machine Learning Lecture 3.2 : Soft Margin SVM Mathematical Derivation
zhlédnutí 182Před 3 lety
Machine Learning Lecture 3.2 : Soft Margin SVM Mathematical Derivation
Machine Learning Lecture 3.1 : Support Vector Machine | Introduction to Hard and Soft Margin SVM31:36Machine Learning Lecture 3.1 : Support Vector Machine | Introduction to Hard and Soft Margin SVM
Machine Learning Lecture 3.1 : Support Vector Machine | Introduction to Hard and Soft Margin SVM
zhlédnutí 98Před 3 lety
Machine Learning Lecture 3.1 : Support Vector Machine | Introduction to Hard and Soft Margin SVM
Machine Learning Lecture 2.1 : Linear Regression Theory and Hands-on with Python31:27Machine Learning Lecture 2.1 : Linear Regression Theory and Hands-on with Python
Machine Learning Lecture 2.1 : Linear Regression Theory and Hands-on with Python
zhlédnutí 85Před 3 lety
Machine Learning Lecture 2.1 : Linear Regression Theory and Hands-on with Python
Lecture 1 - Deep Learning with Python Hands-on : Mcculloch-Pitts Neuron23:42Lecture 1 - Deep Learning with Python Hands-on : Mcculloch-Pitts Neuron
Lecture 1 - Deep Learning with Python Hands-on : Mcculloch-Pitts Neuron
zhlédnutí 721Před 3 lety
Lecture 1 - Deep Learning with Python Hands-on : Mcculloch-Pitts Neuron

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