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Raspberry Pi and Arduino - Go to The Next Level - Activity 07 - Solution
In this video, we will work on the activity solution to send a notification to Telegram when Arduino board is connected. This clip is from the chapter "Part 3 - Practice" of the series "Raspberry Pi and Arduino - Go to the Next Level".In...
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Deep Learning CNN Convolutional Neural Networks with Python - Project Implementation
This video explains the project implementation. This clip is from the chapter "Face Verification" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on building the face verification app.
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Deep Learning CNN Convolutional Neural Networks with Python - MaxPooling Exercise
This is an exercise video on MaxPooling. This clip is from the chapter "Deep Neural Network Architecture" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the deep neural network...
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Deep Learning CNN Convolutional Neural Networks with Python - Implementing Convolution in Python Revisited
This video helps in implementing convolution in Python revisited. This clip is from the chapter "Deep Neural Network Architecture" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the...
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Deep Learning CNN Convolutional Neural Networks with Python - Implementation of Image Blurring Edge Detection Image Sharpening in Python
This video focuses on the process of implementing image blurring edge detection image sharpening in Python. This clip is from the chapter "Image Processing" of the series "Deep Learning CNN: Convolutional Neural Networks with...
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Deep Learning CNN Convolutional Neural Networks with Python - HOG Features
This video demonstrates the features of HOG. This clip is from the chapter "Object Detection" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on the methods of object detection.
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Python for Deep Learning - Build Neural Networks in Python - Data Pre-Processing
In this video, you will learn how data pre-processing works. 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...
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Selenium WebDriver Advanced - Industry Standard Framework - Utilizing Checkpoint Class in Test Method
This video explains utilizing the checkpoint class in test method. This clip is from the chapter "Checkpoint Concept" of the series "Selenium WebDriver Advanced - Industry Standard Framework".In this section, you will learn about the...
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Selenium WebDriver Advanced - Industry Standard Framework - Introduction to BaseTest Class
This video introduces you to the BaseTest class. This clip is from the chapter "Introduction to Base Classes" of the series "Selenium WebDriver Advanced - Industry Standard Framework".In this section, you will learn about base classes.
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Selenium WebDriver Advanced - Industry Standard Framework - How to Set Browser Options
This video explains how to set browser options. This clip is from the chapter "WebDriver Factory Pattern" of the series "Selenium WebDriver Advanced - Industry Standard Framework".In this section, you will learn about WebDriver Factory...
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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...
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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.
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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...
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Reinforcement Learning and Deep RL Python Theory and Projects - Changing the Algorithm
This video talks about changing the algorithm. This clip is from the chapter "Stable Baselines Cartpole Solution" of the series "Reinforcement Learning and Deep RL Python (Theory and Projects)".This section focuses on the Stable...
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Python for Machine Learning - The Complete Beginners Course - Implementation of K-Means Clustering in Python
In this video, you will learn how to implement K-Means clustering 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...
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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...
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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...
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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...
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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...
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Python In Practice - 15 Projects to Master Python - Working with Images
This video helps in working with images. This clip is from the chapter "Advanced Level: Python GUI" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on the advanced level concepts that is on python GUI.
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Python In Practice - 15 Projects to Master Python - Training the Model to Rate Reviews
This video explains training the model to rate reviews. This clip is from the chapter "Rating Bot" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on the Rating Bot.
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Python In Practice - 15 Projects to Master Python - Reviews and Ratings Data to Create the Model
This video explains the reviews and ratings data to create the model. This clip is from the chapter "Rating Bot" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on the Rating Bot.
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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.
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Python In Practice - 15 Projects to Master Python - Importing the Data
This video explains importing the data. This clip is from the chapter "Data Science Project 1" of the series "Python in Practice - 15 Projects to Master Python".This section focuses on data science project 1.