Канал: Practical Data Science and Machine learning

Decision Tree - Regression| How Decision tree works with regression problem?

Decision Tree - Regression| How Decision tree works with regression problem?

Pandas dataframe set_index and reset_index

Pandas dataframe set_index and reset_index

Bidirectional RNN | Bidirectional LSTM | Bidirectional GRU | How they work?

Bidirectional RNN | Bidirectional LSTM | Bidirectional GRU | How they work?

Gini impurity - Decision Tree Classification

Gini impurity - Decision Tree Classification

Decision Tree Classification - ID3 Algorithm

Decision Tree Classification - ID3 Algorithm

Summarizing the paper "Sequence to Sequence learning with Neural Networks"

Summarizing the paper "Sequence to Sequence learning with Neural Networks"

loc and iloc in pandas dataframe | How to select required rows and columns from a pandas dataframe

loc and iloc in pandas dataframe | How to select required rows and columns from a pandas dataframe

Decision Tree - Part1 : What is a decision tree? | Geometric Intuition | Theoretical understanding

Decision Tree - Part1 : What is a decision tree? | Geometric Intuition | Theoretical understanding

Pandas: Different ways to create a Pandas Dataframe

Pandas: Different ways to create a Pandas Dataframe

Pandas: Introduction to Pandas | Pandas Series | Pandas Dataframe

Pandas: Introduction to Pandas | Pandas Series | Pandas Dataframe

Practical Data Science and Machine learning Live Stream

Practical Data Science and Machine learning Live Stream

Sequence2Sequence | Encoder Decoder architecture explained clearly

Sequence2Sequence | Encoder Decoder architecture explained clearly

What is Boxplot | Quartiles | IQR : Inter Quartile Range | min, max | Outliers

What is Boxplot | Quartiles | IQR : Inter Quartile Range | min, max | Outliers

What are Quantiles, Quartiles and Percentiles?

What are Quantiles, Quartiles and Percentiles?

Why regression in logistic regression? #log(odds) #logisticregression #maximumlikelihood #ML

Why regression in logistic regression? #log(odds) #logisticregression #maximumlikelihood #ML

Variance | Standard Deviation | MAD | Coefficient of variation - Measure of dispersion.

Variance | Standard Deviation | MAD | Coefficient of variation - Measure of dispersion.

Implement K-Means clustering in python from scratch

Implement K-Means clustering in python from scratch

Descriptive statistics: Measure of Central Tendency | Mean, Median, Mode, weighted and trimmed mean

Descriptive statistics: Measure of Central Tendency | Mean, Median, Mode, weighted and trimmed mean

Statistics - Gentle Introduction

Statistics - Gentle Introduction

Implement sentiment analysis model using LSTM

Implement sentiment analysis model using LSTM

GRU (Gated Recurrent Unit) - Explained Clearly with indepth math involved

GRU (Gated Recurrent Unit) - Explained Clearly with indepth math involved

LSTM (Long Short Term Memory) - Part 3 | Inner workings of LSTM explained easily with complete math

LSTM (Long Short Term Memory) - Part 3 | Inner workings of LSTM explained easily with complete math

LSTM (Long Short Term Memory) - Part2 | Architecture overview

LSTM (Long Short Term Memory) - Part2 | Architecture overview

LSTM (Long Short Term Memory) RNN - Part1 | Setting up the stage as why we need LSTM RNN

LSTM (Long Short Term Memory) RNN - Part1 | Setting up the stage as why we need LSTM RNN

Different types of RNN Architectures

Different types of RNN Architectures

Implement a simple Language model using RNN in Keras-Part2

Implement a simple Language model using RNN in Keras-Part2

Implement a simple Language model using RNN in Keras-Part1

Implement a simple Language model using RNN in Keras-Part1

Language Model Using RNN - Theory explained with an example.

Language Model Using RNN - Theory explained with an example.

Issues with Recurrent Neural Networks

Issues with Recurrent Neural Networks

Tutorial 10: Recurrent Neural Network Back Propagation in Time

Tutorial 10: Recurrent Neural Network Back Propagation in Time

Tutorial 9: Recurrent Neural Networks - Forward Propagation with Maths

Tutorial 9: Recurrent Neural Networks - Forward Propagation with Maths

Tutorial 8: Recurrent Neural Networks (RNN) - Introduction | Why RNN | Why not ANN

Tutorial 8: Recurrent Neural Networks (RNN) - Introduction | Why RNN | Why not ANN

Activation Functions-Part2 | Sigmoid | Tanh | ReLu | LeakyReLu Explained in detail

Activation Functions-Part2 | Sigmoid | Tanh | ReLu | LeakyReLu Explained in detail

Tutorial 8 : Exploding Gradients | Deep learning | Neural Networks

Tutorial 8 : Exploding Gradients | Deep learning | Neural Networks

Tutorial 7: Vanishing Gradients | Deep learning | Neural Network | Sigmoid | weights initialization

Tutorial 7: Vanishing Gradients | Deep learning | Neural Network | Sigmoid | weights initialization

Tutorial 6: Apply Gradient Descent to Neural Networks | Deep Learning

Tutorial 6: Apply Gradient Descent to Neural Networks | Deep Learning

Activation Functions-Part1 | Sigmoid | tanh | ReLu | Leaky ReLu| Softmax

Activation Functions-Part1 | Sigmoid | tanh | ReLu | Leaky ReLu| Softmax

Tutorial 5: How to setup and train the neural networks | Putting bits and pieces together

Tutorial 5: How to setup and train the neural networks | Putting bits and pieces together

Tutorial 4: Back propagation in Neural Networks | Chain rule of derivatives

Tutorial 4: Back propagation in Neural Networks | Chain rule of derivatives

Tutorial 3: How Neural Network Learns-Part1 | Loss Function | Cost Function

Tutorial 3: How Neural Network Learns-Part1 | Loss Function | Cost Function

Tutorial 2: Neural Network Forward Propagation | Forward Pass | computations

Tutorial 2: Neural Network Forward Propagation | Forward Pass | computations

Tutorial 1: Introduction to Artificial Neural Networks | Deep Learning | ANN

Tutorial 1: Introduction to Artificial Neural Networks | Deep Learning | ANN

Implement Email spam classifier in python

Implement Email spam classifier in python

Tutorial 7: Gensim Word2Vec | Train Gensim Word2Vec on your own dataset | Customize as per your Data

Tutorial 7: Gensim Word2Vec | Train Gensim Word2Vec on your own dataset | Customize as per your Data

Tutorial 4: Stemming and Lemmatizing

Tutorial 4: Stemming and Lemmatizing

Tutorial 6: Word2Vec - Part2. In depth explanation on how embeddings are learnt

Tutorial 6: Word2Vec - Part2. In depth explanation on how embeddings are learnt

Tutorial 5: Word2Vec - Part1

Tutorial 5: Word2Vec - Part1

Tutorial 1: nltk Tokenization. Nltk sent_tokenizer, Nltk.Wordtokenizer

Tutorial 1: nltk Tokenization. Nltk sent_tokenizer, Nltk.Wordtokenizer

Tutorial 3: NLP : TF IDF (Term Frequency Inverse Document Frequency)

Tutorial 3: NLP : TF IDF (Term Frequency Inverse Document Frequency)

Tutorial 2: NLP: Bag of Words (BoW) | Sklearn Count Vectorizer

Tutorial 2: NLP: Bag of Words (BoW) | Sklearn Count Vectorizer

NLP Intro

NLP Intro

K means clustering - Introduction

K means clustering - Introduction

Regularization: Ridge and Lasso (Avoid overfitting), with in depth math intuition.

Regularization: Ridge and Lasso (Avoid overfitting), with in depth math intuition.

Principal Component Analysis - Explained easily

Principal Component Analysis - Explained easily

SVM KERNELS

SVM KERNELS

list comprehension in python

list comprehension in python

SVM Cost function and complete math behind large margin | Support vector machine

SVM Cost function and complete math behind large margin | Support vector machine

SVM | Support Vector Machine - Part 1

SVM | Support Vector Machine - Part 1

scikit-learn: Linear regression implementation | sklearn

scikit-learn: Linear regression implementation | sklearn

Model Bias and Model Variance Explained clearly | Machine learning Model

Model Bias and Model Variance Explained clearly | Machine learning Model

Train data + validation data + test data | data split in Machine learning

Train data + validation data + test data | data split in Machine learning

Implement KNN Regression from scratch in python

Implement KNN Regression from scratch in python

K Nearest Neighbors - issues and solution

K Nearest Neighbors - issues and solution

KNN Regression and Classification | K Nearest Neighbors - Introduction

KNN Regression and Classification | K Nearest Neighbors - Introduction

Distance Metrics | Euclidean distance | Manhattan distance | Minkowski distance|

Distance Metrics | Euclidean distance | Manhattan distance | Minkowski distance|

Logistic Regression - Decision Boundary

Logistic Regression - Decision Boundary

7. R square and Adjusted R square

7. R square and Adjusted R square

Classification metrics | Confusion matrix, precision, recall and F1 Score

Classification metrics | Confusion matrix, precision, recall and F1 Score

Implement Logistic regression + gradient descent in python from scratch

Implement Logistic regression + gradient descent in python from scratch

Apply Gradient descent to Logistic regression

Apply Gradient descent to Logistic regression

6. Linear Regression Assumptions

6. Linear Regression Assumptions

Logistic regression log odds and Maximum likelihood

Logistic regression log odds and Maximum likelihood

Logistic regression cost function | In depth math intuition

Logistic regression cost function | In depth math intuition

Logistic regression | Math behind sigmoid function | hypothesis part 2

Logistic regression | Math behind sigmoid function | hypothesis part 2

Logistic regression | Binary Classification | hypothesis part1

Logistic regression | Binary Classification | hypothesis part1

How to avoid for loops | Vectorization in Machine learning

How to avoid for loops | Vectorization in Machine learning

Implement Linear regression + gradient descent in python from scratch | univariate linear regression

Implement Linear regression + gradient descent in python from scratch | univariate linear regression

4. Linear Regression | Multiple features/variables

4. Linear Regression | Multiple features/variables

what are reshape and squeeze methods in NumPy?

what are reshape and squeeze methods in NumPy?

5. Apply gradient descent to linear regression

5. Apply gradient descent to linear regression

5. Gradient Descent Machine learning Algorithm End to End part2

5. Gradient Descent Machine learning Algorithm End to End part2

4. Gradient Descent Machine learning part1 intuition

4. Gradient Descent Machine learning part1 intuition

3. Linear Regression-part3-Loss and cost function (Mean Squared Error)

3. Linear Regression-part3-Loss and cost function (Mean Squared Error)

2. Linear Regression-part2-Notations

2. Linear Regression-part2-Notations

1. Linear Regression-part1-Univariate Hypothesis intuition

1. Linear Regression-part1-Univariate Hypothesis intuition

Machine learning and Deep learning Topics

Machine learning and Deep learning Topics

Tutorial 11 for loop and while loop in python

Tutorial 11 for loop and while loop in python

Tutorial 10 Python if, else, if/elif

Tutorial 10 Python if, else, if/elif

NumPy Tutorial 6 ravel() and flatten() methods of NumPy

NumPy Tutorial 6 ravel() and flatten() methods of NumPy

Read values from keyboard in Python

Read values from keyboard in Python

NumPy Tutorial 5 min(), max(), argmin() and argmax() on NumPy Arrays

NumPy Tutorial 5 min(), max(), argmin() and argmax() on NumPy Arrays

NumPy Tutorial 4 Using all() and any() methods of NumPy for conditional execution

NumPy Tutorial 4 Using all() and any() methods of NumPy for conditional execution

NumPy Tutorial 3 Understanding all() and any() methods of NumPy

NumPy Tutorial 3 Understanding all() and any() methods of NumPy

NumPy Tutorial 2 Understanding multidimensional NumPy arrays and their shape

NumPy Tutorial 2 Understanding multidimensional NumPy arrays and their shape

NumPy Tutorial 1 Introduction to NumPy Arrays

NumPy Tutorial 1 Introduction to NumPy Arrays

Channel Intro

Channel Intro

Slice and Dice in Python

Slice and Dice in Python

Tutorial 9 Python tuples

Tutorial 9 Python tuples

Tutorial 8 Python dictionaries

Tutorial 8 Python dictionaries

Python Shallow Copy VS Deep Copy

Python Shallow Copy VS Deep Copy

Tutorial 7 Python sets part2

Tutorial 7 Python sets part2

Tutorial 6 Python sets part1

Tutorial 6 Python sets part1

Tutorial 5 Python lists continued

Tutorial 5 Python lists continued

Tutorial 4 Python lists

Tutorial 4 Python lists

How to start Jupyter notebook and basics of jupyter notebook

How to start Jupyter notebook and basics of jupyter notebook

Anaconda installation and basic commands

Anaconda installation and basic commands

Tutorial 3 Python strings continued

Tutorial 3 Python strings continued

Tutorial 1 Python intro

Tutorial 1 Python intro

Tutorial 2 Python strings

Tutorial 2 Python strings