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Practical Data Science using Python - Logistic Regression Introduction
This video introduces you to logistic regression. This clip is from the chapter "Logistic Regression" of the series "Practical Data Science Using Python".This section explains logistic regression.
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Practical Data Science using Python - Linear Regression Data Preparation and Analysis 3
This video explains the train-rest split and feature scaling. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.
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Practical Data Science using Python - Linear Regression Car Price Prediction
This video explains linear regression car price prediction. This clip is from the chapter "Linear Regression" of the series "Practical Data Science Using Python".This section explains linear regression.
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Practical Data Science using Python - EDA Tools and Processes
This video explains EDA tools and processes. This clip is from the chapter "Exploratory Data Analysis (EDA)" of the series "Practical Data Science Using Python".This section explains Exploratory Data Analysis.
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Practical Data Science using Python - Decision Tree - Iris Dataset Case Study
This video explains decision tree - Iris Dataset case study. This clip is from the chapter "Classification using decision trees" of the series "Practical Data Science Using Python".This section explains classification using decision trees.
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Deep Learning CNN Convolutional Neural Networks with Python - Training DNN Animation
This video talks about training DNN animation. 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 overview of the deep...
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Python for Deep Learning - Build Neural Networks in Python - Training and Test Sets: Splitting Data
In this video, we will be working on splitting the data with training and test sets. This clip is from the chapter "Implementation of ANN in Python" of the series "Python for Deep Learning — Build Neural Networks in Python".In this...
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Python for Deep Learning - Build Neural Networks in Python - Exploring the Dataset
In this video, you will learn how to explore the dataset. This clip is from the chapter "Implementation of ANN in Python" of the series "Python for Deep Learning — Build Neural Networks in Python".In this section, you will learn how to...
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Machine Learning Random Forest with Python from Scratch - Introduction to the Final Project
In this video, we will discuss our final project, which classifies the titanic dataset using Random Forest. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with Python from...
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Machine Learning Random Forest with Python from Scratch - Information Gain
In this video, we will define columns for questioning and determine how much information can be gained by splitting a column. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with...
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Machine Learning Random Forest with Python from Scratch - Accuracy and Error - Random Forest Step-by-Step
In this video, you will learn to implement the accuracy method to help determine our model's performance. This clip is from the chapter "Random Forest Step-by-Step" of the series "Machine Learning: Random Forest with Python from...
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Selenium WebDriver Advanced - Industry Standard Framework - How to Manage Test Data in Excel File
This video explains how to manage test data in an Excel file. This clip is from the chapter "Data-Driven Testing" of the series "Selenium WebDriver Advanced - Industry Standard Framework".In this section, you will learn about data-driven...
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Reinforcement Learning and Deep RL Python Theory and Projects - Setting Up Environment
This video explains setting up the environment. 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.
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Reinforcement Learning and Deep RL Python Theory and Projects - DNN Gradient Descent Stochastic Batch Minibatch
This video explains about the gradient descent Stochastic Batch Minibatch. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Models and Optimization: Machine Learning Model 2
In this video, we will cover machine learning model 2. This clip is from the chapter "Machine Learning: Machine Learning Crash Course" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we...
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Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Clustering
In this video, we will cover clustering. This clip is from the chapter "Machine Learning: Machine Learning Crash Course" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will cover...
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Data Science and Machine Learning (Theory and Projects) A to Z - Transfer Learning: ImageNet Challenge
In this video, we will cover ImageNet challenge. This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we...
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Data Science and Machine Learning (Theory and Projects) A to Z - Random Variables: Random Variables in Real Datasets
In this video, we will cover random variables in real datasets. This clip is from the chapter "Basics for Data Science: Mastering Probability and Statistics in Python" of the series "Data Science and Machine Learning (Theory and...
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Data Science and Machine Learning (Theory and Projects) A to Z - Project I_ Book Writer: Modelling RNN Model Training
In this video, we will cover modelling RNN model training. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...
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Data Science and Machine Learning (Theory and Projects) A to Z - Geographic Maps with Folium: Geographic Maps with Folium using COVID-19 Data Solution
In this video, we will cover geographic maps with Folium using COVID-19 data solution. This clip is from the chapter "Basics for Data Science: Data Understanding and Data Visualization with Python" of the series "Data Science and Machine...
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Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Categorical Features
In this video, we will cover categorical features. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to...
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Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: DNN Training Parameters
In this video, we will cover DNN training parameters. This clip is from the chapter "Deep learning: Artificial Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section,...
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Fundamentals of Machine Learning - Tree-Based Methods - Part 2
The second part of the tree-based methods explains random forests. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of statistical learning, sampling, and...
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Fundamentals of Machine Learning - Linear Regression - Labs
This video explains linear regression using an example of predicting fuel efficiency. This clip is from the chapter "Labs" of the series "Fundamentals of Machine Learning".This section explains the various lab exercises on linear...