Curated Video
Practical Data Science using Python - Decision Tree - Gini Index and Entropy Measures
This video explains decision tree - Gini Index and Entropy Measures. This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains classification using...
Curated Video
Reinforcement Learning and Deep RL Python Theory and Projects - Perceptron Implementation
This video explains the implementation of Perceptron. This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN foundation...
Curated Video
Reinforcement Learning and Deep RL Python Theory and Projects - Loading the Data
This video explains how to load the data. This clip is from the chapter "Trading Bot RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the Trading Bot RL.
Curated Video
Reinforcement Learning and Deep RL Python Theory and Projects - DNN PyTorch CIFAR10 Example
This video talks about the example of DNN PyTorch CIFAR10. This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...
Curated Video
Reinforcement Learning and Deep RL Python Theory and Projects - DNN Implementation Stochastic Gradient Descent
This video explains about the implementation of stochastic gradient descent. This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses...
Curated Video
Reinforcement Learning and Deep RL Python Theory and Projects - DNN Implementation in PyTorch
This video explains about the implementation in PyTorch. This clip is from the chapter "DNN Foundation for Deep RL" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the DNN...
Curated Video
Python for Machine Learning - The Complete Beginners Course - K-Nearest Neighbors (KNN) Using Python
In this video, we will cover K-Nearest Neighbors (KNN) using Python. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Introduction to Decision Trees
In this video, we will have a quick introduction to decision trees. This clip is from the chapter "Classification Algorithms: Decision Tree" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Splitting Data into Train and Test Sets - Classification Algorithms: K-Nearest Neighbors
In this video, you will learn how to split data into train and test sets. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Pre-Processing
In this video, you will learn how to do pre-processing. This clip is from the chapter "Classification Algorithms: Logistic Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Importing the Dataset
In this video, you will learn how to import the dataset. This clip is from the chapter "Classification Algorithms: K-Nearest Neighbors" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Importing Libraries and Datasets - Recommender System
In this video, you will learn how to import libraries and datasets. This clip is from the chapter "Recommender System" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, we will cover the...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python: Importing Libraries and Datasets - Classification Algorithms: Logistic Regression
In this video, you will learn how to import libraries and datasets. This clip is from the chapter "Classification Algorithms: Logistic Regression" of the series "Python for Machine Learning - The Complete Beginner's Course".In this...
Curated Video
Python for Machine Learning - The Complete Beginners Course - Implementation in Python
In this video, you will learn implementation in Python. This clip is from the chapter "Clustering" of the series "Python for Machine Learning - The Complete Beginner's Course".In this section, you will learn about clustering.
Curated Video
Python In Practice - 15 Projects to Master Python - Preparing the Data
This video explains preparing the data. This clip is from the chapter "Flavor Predictor" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on the flavor predictor.
Curated Video
Python In Practice - 15 Projects to Master Python - Creating a Machine Learning Model with Dataset
This video helps in creating a machine learning model with a dataset. This clip is from the chapter "Machine Learning with Python" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on machine learning...
Packt
Python Data Types: Understanding and Storing Data Structures in Python
In this video, we delve into the topic of data structures in Python. From academic results to online orders, everything is data that holds value and requires proper storage. Without structuring it correctly, the data can easily turn into...
Curated Video
Machine Learning Random Forest with Python from Scratch - Reading and Manipulating Dataset
Previously, you learned how to read a dataset; now, we will look at manipulating the data and using a sample dataset in our code. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest...
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Machine Learning Random Forest with Python from Scratch - Outliers Removal
In the second part of the data cleaning process, we will look at an outlier in detail and learn how to correct or remove the outlier. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random...
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Machine Learning Random Forest with Python from Scratch - Impurity
Like all dataset characteristics, we will look at the impurities in a dataset and how they should be minimum in a good dataset. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest...
Curated Video
Machine Learning Random Forest with Python from Scratch - Best Slip
Here, we will determine the best split at any decision node where information is maximum and split into two branches, true and false. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random...
Packt
Fundamentals of Neural Networks - Welcome Message
This video explains the need for taking up the course and introduces you to the author. This clip is from the chapter "Welcome" of the series "Fundamentals in Neural Networks".This section introduces you to the course and the course...
Packt
Fundamentals of Neural Networks - Padding
This video explains padding in convolutional neural networks. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you...
Packt
Fundamentals of Neural Networks - Language Processing
NLP is a tool for structuring data in a way that AI systems can process that deals with language. NLP uses AI to 'read' through a document and extract key information. This clip is from the chapter "Recurrent Neural Networks" of the...