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Comprehensive Android Developer Bootcamp - Listviews vs RecyclerViews
Android Listviews and RecyclerView Widgets:Listviews vs RecyclerViews This clip is from the chapter "Android Listviews and RecyclerView Widgets" of the series "The Comprehensive Android Developer Bootcamp".This section shows how to work...
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REST API Automation Testing from Scratch - REST Assured Java - Example on Parameterization of API Tests with Multiple Datasets
This video presents an example on parameterization of API tests with multiple datasets. This clip is from the chapter "Handling Dynamic JSON Payloads with Parameterization" of the series "REST API Automation Testing from Scratch - REST...
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PySpark and AWS: Master Big Data with PySpark and AWS - Solution (Average)
Let's discuss a solution for the quiz on average. This clip is from the chapter "Spark RDDs" of the series "PySpark and AWS: Master Big Data with PySpark and AWS".This section focuses on PySpark RDDs.
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PySpark and AWS: Master Big Data with PySpark and AWS - Projects Overview
This video provides a brief description of the various projects we will be building together. This clip is from the chapter "Introduction" of the series "PySpark and AWS: Master Big Data with PySpark and AWS".Welcome to the course. This...
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pandas for Python - A Quick Guide - Processing String Format
In this lesson, we will continue processing data, but this time with string format data. String features have their operations. We will look at all the powerful tools on Pandas for handling string data. This clip is from the chapter...
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No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Building and Using the Model for Prediction - Project 1 - Banknote Authentication
In this video, you will learn how to build and use the model for prediction. This clip is from the chapter "Project 1 - Banknote Authentication" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".In this section,...
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No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Building the Model - Project 4 - Wine Quality Prediction
In this video, you will learn how to build the model. This clip is from the chapter "Project 4 - Wine Quality Prediction" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".In this section, we will work on a...
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No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Adding and Joining Datasets
In this video, you will learn how to add and join datasets. This clip is from the chapter "Project 4 - Wine Quality Prediction" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".In this section, we will work on a...
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No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Getting Datasets for Practice
In this video, you will learn how to get datasets for practice. This clip is from the chapter "Congratulations and Next Steps" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".Welcome to the last section of our...
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Data Analytics using Python Visualizations - Plotting Regression Lines with OLS (ML)
This video explains plotting regression lines with OLS (ML). This clip is from the chapter "Advanced Visualizations Using Business Applications" of the series "Data Analytics Using Python Visualizations".This section explains advanced...
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Data Analytics using Python Visualizations - Stock Trend / Time Series Plot and Annotations
This video explains stock trend / time series plot and annotations. This clip is from the chapter "Matplotlib and Seaborn – Libraries and Techniques" of the series "Data Analytics Using Python Visualizations".This section introduces...
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Python for Machine Learning - The Complete Beginners Course - Importing the Dataset
In this video, you will learn how to import the dataset. 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.
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Practical Data Science using Python - Support Vector Machine - Classifying Polynomial Data
This video explains Support Vector Machine - classifying polynomial data. This clip is from the chapter "Advanced Classification Techniques – Support Vector Machine" of the series "Practical Data Science Using Python".This section...
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Practical Data Science using Python - Random Forest - Model Building and Hyperparameter Tuning using Grid Search CV
This video explains random forest - model building and hyperparameter tuning using grid search CV. This clip is from the chapter "Ensemble Methods – Random Forest" of the series "Practical Data Science Using Python".This section explains...
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Practical Data Science using Python - Pandas DataFrame 2
This video explains the describe() DataFrame command. 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.
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Practical Data Science using Python - Logistic Regression - Telecom Churn Case Study
This video explains logistic regression - Telecom Churn case study. 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 - Logistic Regression - Model Optimization 2
This video demonstrates how to predict the level by taking 0.3 as the optimum threshold. 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 - Feature Scaling and Cost Functions
This video explains linear regression - feature scaling and cost functions. 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 Project - 2
This video explains data distribution. 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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Deep Learning CNN Convolutional Neural Networks with Python - ImageNet Challenge
This video talks about the challenges with ImageNet. This clip is from the chapter "Transfer Learning" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section focuses on transfer learning.
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Deep Learning CNN Convolutional Neural Networks with Python - DNN Training Parameters
This video explains the DNN training parameters. 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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Deep Learning CNN Convolutional Neural Networks with Python - Batch MiniBatch Stochastic Gradient Descent
This video explains batch MiniBatch stochastic gradient descent. 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...
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Data Science and Machine Learning (Theory and Projects) A to Z - Deep Neural Networks and Deep Learning Basics: Training DNN Animation
In this video, we will cover training DNN animation. 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, we...
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Complete SAS Programming Guide - Learn SAS and Become a Data Ninja - Decile Calibration Plot
This video talks about decile calibration plot. This clip is from the chapter "SAS Predictive Modeling, Evaluation Metrics" of the series "Complete SAS Programming Guide - Learn SAS and Become a Data Ninja".This section focuses on SAS...