This video explains the Probability Theory.<br<br/>/>

This clip is from the chapter "Statistical Techniques" of the series "Practical Data Science Using Python".This section explains advanced visualizations using business applications.

This video demonstrates PCA using Python.<br<br/>/>

This clip is from the chapter "Dimensionality Reduction Using PCA" of the series "Practical Data Science Using Python".This section explains dimensionality reduction using PCA.

This video explains the round method.<br<br/>/>

This clip is from the chapter "Python for Data Science" of the series "Practical Data Science Using Python".This section explains Python for data science.

This video explains between the various methods in Pandas series.<br<br/>/>

This clip is from the chapter "Python for Data Science" of the series "Practical Data Science Using Python".This section explains Python for data science.

This video explains the Pandas series.<br<br/>/>

This clip is from the chapter "Python for Data Science" of the series "Practical Data Science Using Python".This section explains Python for data science.

This video explains filling missing values in dataframe.<br<br/>/>

This clip is from the chapter "Python for Data Science" of the series "Practical Data Science Using Python".This section explains Python for data science.

This video explains Pandas DataFrame.<br<br/>/>

This clip is from the chapter "Python for Data Science" of the series "Practical Data Science Using Python".This section explains Python for data science.

This video explains optimizing classification metrics.<br<br/>/>

This clip is from the chapter "Machine Learning" of the series "Practical Data Science Using Python".This section explains machine learning.

This video introduces you to logistic regression.<br<br/>/>

This clip is from the chapter "Logistic Regression" of the series "Practical Data Science Using Python".This section explains logistic regression.

This video introduces you to deep learning.<br<br/>/>

This clip is from the chapter "Introduction to Deep Learning" of the series "Practical Data Science Using Python".This section explains deep learning.

This video explains logistic regression - model optimization.<br<br/>/>

This clip is from the chapter "Logistic Regression" of the series "Practical Data Science Using Python".This section explains logistic regression.

This video explains the train-rest split and feature scaling.<br<br/>/>

This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.

This video explains how to plot the distribution of various values of engine types.<br<br/>/>

This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.

This video explains linear regression car price prediction.<br<br/>/>

This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.

This video explains linear regression - practical approach.<br<br/>/>

This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.

This video explains linear regression - cost functions and gradient descent.<br<br/>/>

This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.

This video explains EDA tools and processes.<br<br/>/>

This clip is from the chapter "Exploratory Data Analysis (EDA)" of the series "Practical Data Science Using Python".This section explains Exploratory Data Analysis.

This video explains the correlation between grade of loan and default ratio.
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This clip is from the chapter "Exploratory Data Analysis (EDA)" of the series "Practical Data Science Using Python".This section explains...

This video explains decision tree - Iris Dataset case study.
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This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains classification using...

This video explains the Binomial Theory - expected value and standard error.
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This clip is from the chapter "Statistical Techniques" of the series "Practical Data Science Using Python".This section explains advanced...

This video explains calculating number of weights of DNN.
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This clip is from the chapter "Deep Neural Network Overview" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the...

Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. LSTM networks are well-suited to classifying, processing, and making predictions based on time series data...

In this video, you will learn how to update weights in Python.
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This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive deeper...

In this video, you will learn how to implement logistic regression.
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This clip is from the chapter "Deep Learning" of the series "Deep Learning - Deep Neural Network for Beginners Using Python".In this section, we will dive...