Instructional Video3:49
Curated Video

Project Based Learning

Higher Ed
Project-Based Learning is a method that involves students in a long-term in-depth investigation of a real world challenge. Instead of raw memorization of facts or following instructions that present a smooth path to knowledge, students...
Instructional Video6:26
Curated Video

Project-Based Learning: How It Works and Why It’s So Effective

Higher Ed
The video is about project-based learning (PBL), which is described as a powerful way to learn new things and remember them for a long time. The video also provides an example of a shy 19-year-old student named Jane who wanted to move...
Instructional Video14:24
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Mathematical Foundation: Coordinates Versus Dimensions

Higher Ed
In this video, we will cover coordinates versus dimensions. 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...
Instructional Video6:36
Brainwaves Video Anthology

Jane Krauss - Computer Science for All A Few Reasons Why

Higher Ed
Jane Krauss is a teacher, author and consultant who does curriculum and program development designed to increase participation of girls and other underrepresented groups in computer science. She will gladly tell you why computational...
Instructional Video52:11
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Project Bayes Classifier: Project Bayes Classifier from Scratch

Higher Ed
In this video, we will cover project Bayes Classifier from scratch. 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...
Instructional Video8:40
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Similarity Based Methods Introduction

Higher Ed
In this video, we will cover similarity based methods introduction. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory...
Instructional Video5:37
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Python Useful function: Python Function- Round

Higher Ed
In this video, we will cover Python function- round. 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 Z".In...
Instructional Video18:55
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Statistical Based Methods

Higher Ed
In this video, we will cover statistical based methods. 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)...
Instructional Video11:42
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Similarity Based Methods Criteria

Higher Ed
In this video, we will cover similarity based methods criteria. 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...
Instructional Video10:09
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - String in Python: String Escape Sequences

Higher Ed
In this video, we will cover string escape sequences. 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 Z".In...
Instructional Video5:49
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Introduction to Machine Learning: Unsupervised Learning

Higher Ed
In this video, we will cover unsupervised learning. 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...
Instructional Video10:43
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Process of Learning from Data: Unsupervised Learning and Reinforcement Learning

Higher Ed
In this video, we will cover unsupervised learning and reinforcement learning. 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...
Instructional Video4:24
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Installation of Anaconda and IPython Shell: Installing Python and Jupyter Anaconda

Higher Ed
In this video, we will be installing Python and Jupyter Anaconda. 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...
Instructional Video8:06
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Function and Module in Python: Variable Number of Input Arguments as Dictionary

Higher Ed
In this video, we will cover variable number of input arguments as dictionary. 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...
Instructional Video9:44
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Function and Module in Python: Multiple Input Arguments

Higher Ed
In this video, we will cover multiple input arguments. 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 Z".In...
Instructional Video8:53
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Function and Module in Python: Input Arguments

Higher Ed
In this video, we will cover input arguments. 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 Z".In this...
Instructional Video6:28
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Probability Model: Probability Models BayesRule

Higher Ed
In this video, we will cover probability models BayesRule. 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 Projects) A...
Instructional Video12:45
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Continuous Random Variables: Transformation of Random Variables

Higher Ed
In this video, we will cover transformation of random variables. 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...
Instructional Video6:17
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Probability Model: Probability Models More Examples

Higher Ed
In this video, we will cover probability models more examples. 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 Projects)...
Instructional Video12:46
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Pandas for Data Manipulation and Understanding: Pandas Merge

Higher Ed
In this video, we will cover Pandas Merge. This clip is from the chapter "Basics for Data Science: Data Understanding and Data Visualization with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In...
Instructional Video4:33
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Clustering

Higher Ed
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...
Instructional Video12:00
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Vanishing Gradients in RNN: GRU

Higher Ed
In this video, we will cover GRU. 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 section, we will cover deep...
Instructional Video3:55
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: Fixed Length Memory Model Exercise Solution Part 02

Higher Ed
In this video, we will cover fixed length memory model exercise solution part 02. This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects)...
Instructional Video5:13
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Filter Methods

Higher Ed
In this video, we will cover filter methods. 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...

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