Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Versus Matplotlib Style
In this video, we will cover Seaborn versus Matplotlib Style. This clip is from the chapter "Basics for Data Science: Python for Data Science and Data Analysis" of the series "Data Science and Machine Learning (Theory and Projects) A to...
Curated Video
AWS Certified Data Analytics Specialty 2021 - Hands-On! - Choosing Visualization Types
This video explains how to select the visualization types in Amazon QuickSight. This clip is from the chapter "Domain 5: Visualization" of the series "AWS Certified Data Analytics Specialty 2021 "Hands-On!".In this section, you will...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: SubSpace
In this video, we will cover SubSpace. 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 Z".In this...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Classification Practice with Python
In this video, we will cover classification practice with Python. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to TensorFlow: FashionMNIST Example Plan Neural Network
In this video, we will cover FashionMNIST example plan neural network. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Features
In this video, we will cover features. 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 machine...
KnowMo
Problem Solving with Descriptive Statistics
The video is a lecture on problem solving descriptive statistics questions, focusing on the mean, median, mode and range. The instructor works through two examples and emphasizes the importance of logical thinking and interpretation of...
IDG TECHtalk
How to use the dtplyr package
The dtplyr 1.0 package lets you write dplyr R code and access speedy data.table performance. Find out how.
Curated Video
Practical GraphQL - Become a GraphQL Ninja - Introduction to GraphQL
Introduction: Introduction to GraphQL This clip is from the chapter "Introduction" of the series "Practical GraphQL - Become a GraphQL Ninja".This section gives an introduction to GraphQL and creates the application shell.
Curated Video
Selenium Python Automation Testing from Scratch and Frameworks - Implementing Data-Driven Mechanism
This video explains how to implement data-driven mechanism. This clip is from the chapter "Part III-Developing End-to-End Selenium Python Framework from Scratch" of the series "Selenium Python Automation Testing from Scratch and...
Curated Video
PySpark and AWS: Master Big Data with PySpark and AWS - Finding Average-1
In this session, we will try to calculate the average of a given dataset. We will start by writing a transformation flow that will take the CSV data file as input and provide us with the average of the movie ratings from the dataset....
Curated Video
pandas for Python - A Quick Guide - Handling Missing Values and Duplicates
During the data analysis, significant time is spent on data cleaning and transformation. Pandas provides the tool to handle such data. In this video, you will learn about handling missing data and duplicates. You will learn to eliminate...
Curated Video
No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Predicting Data and Validating Accuracy
In this video, you will learn how to predict data and validate the accuracy. This clip is from the chapter "Project 2 - Spam SMS Detection" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".In this section, we...
Curated Video
No-Code Machine Learning Using Amazon AWS SageMaker Canvas - Set Up Data in S3 Buckets for Use in SageMaker
In this video, you will learn how to set up data in S3 Buckets for use in SageMaker. This clip is from the chapter "Setup" of the series "No-Code Machine Learning Using Amazon AWS SageMaker Canvas".In this section, you will learn how to...
Curated Video
Probability Statistics - The Foundations of Machine Learning - Spam Detection - Implementation Issues
In this video, we will cover spam detection - implementation issues. This clip is from the chapter "Applications and Rules for Probability" of the series "Probability / Statistics - The Foundations of Machine Learning".In this section,...
Curated Video
Deep Learning CNN Convolutional Neural Networks with Python - Focus of the Course
This video provides an extension and focus areas about this course in detail. This clip is from the chapter "Introduction to the Course" of the series "Deep Learning CNN: Convolutional Neural Networks with Python".This section provides...
Curated Video
Deep Learning CNN Convolutional Neural Networks with Python - Face Verification Activity
This is an activity video on face verification. 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.
Curated Video
Python for Deep Learning - Build Neural Networks in Python - Introduction - Implementation of ANN in Python
In this video, we will have a quick Introduction to this section. 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...
Curated Video
Python for Deep Learning - Build Neural Networks in Python - Building the CNN Model
In this video, you will learn how to build the Convolutional Neural Networks (CNN) model. This clip is from the chapter "Implementation of CNN in Python" of the series "Python for Deep Learning — Build Neural Networks in Python".In...
Curated Video
Practical Data Science using Python - Unsupervised Learning - K-Means Clustering
This video introduces you to K-Means clustering. This clip is from the chapter "Unsupervised Learning - K-Means Clustering" of the series "Practical Data Science Using Python".This section explains unsupervised learning - K-Means...
Curated Video
Practical Data Science using Python - Support Vector Machine Project 1
This video explains the Support Vector Machine project. This clip is from the chapter "Advanced Classification Techniques – Support Vector Machine" of the series "Practical Data Science Using Python".This section explains advanced...
Curated Video
Practical Data Science using Python - Support Vector Machine Metrics and Polynomial SVM
This video explains Support Vector Machine metrics and polynomial SVM. This clip is from the chapter "Advanced Classification Techniques – Support Vector Machine" of the series "Practical Data Science Using Python".This section explains...
Curated Video
Practical Data Science using Python - Principal Component Analysis - Computations 2
This video explains Eigenvalues and Eigenvectors. 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.
Curated Video
Practical Data Science using Python - Principal Component Analysis - Computations 1
This video explains Principal Component Analysis – computations. This clip is from the chapter "Dimensionality Reduction Using PCA" of the series "Practical Data Science Using Python".This section explains dimensionality reduction using...