Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Features in Data Science: Why Dimensionality Reduction
In this video, we will understand why dimensionality reduction is needed. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Features in Data Science: Features Dimensions
In this video, we will cover features 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 Projects) A to...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Similarity Based Methods Introduction
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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Feature Extraction: Kernel PCA
In this video, we will cover Kernel PCA. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Feature Extraction: Encoder Decoder Networks for Dimensionality Reduction Versus Kernel PCA
In this video, we will cover encoder decoder networks for dimensionality reduction versus Kernel PCA. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Expectations: Law of Large Numbers Famous Distributions Python
In this video, we will cover law of large numbers famous distributions Python. This clip is from the chapter "Basics for Data Science: Mastering Probability and Statistics in Python" of the series "Data Science and Machine Learning...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Expectations: Law of Large Numbers
In this video, we will cover law of large numbers. 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 to Z".In...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Data Preparation and Preprocessing: Data Standardization
In this video, we will cover data standardization. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Applications of RNN (Motivation): Activity
In this video, we will cover activity. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Feature Selection: Why Feature Selection
In this video, we will understand why feature selection is needed. This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - RNN Architecture: OneToMany Model
In this video, we will cover OneToMany model. 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...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Overfitting, Underfitting, and Generalization: Overfitting Example in Python
In this video, we will cover an overfitting example in 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 - Optional Estimation: MLE
In this video, we will cover MLE.
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Optional Estimation: Loglikelihood
In this video, we will cover Loglikelihood.
Curated Video
AWS Certified Data Analytics Specialty 2021 - Hands-On! - [Exercise] Elastic MapReduce - Part 1
This video explains how to use Apache Spark and MLLib (its machine learning library) on an Amazon EMR cluster to consume the order data in an Amazon S3 data lake and produce product recommendations for the customers. This clip is from...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Sets: Cardinality of a Set
In this video, we will cover cardinality of a set. 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 to Z".In...
Curated Video
Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Methods: Features Practice with Python
In this video, we will cover features 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 section,...
Food Farmer Earth
How to Roast Chestnuts
Organic chestnut farmer, Chris Foster demonstrates how to roast fresh chestnuts. Chestnut season runs between October and December. This is the time of year to enjoy roast chestnuts at their peak of freshness over the holiday season.
Professor Dave Explains
Performing Thin Layer Chromatography (TLC)
We've learned a few separation techniques, so how about one more? Chromatography separates components of a mixture by virtue of their differing polarities, and thin layer chromatography, or TLC, is an invaluable technique that is used...
The Business Professor
Marketing - What Distorts the Results of Marketing Research
This Video Explains Marketing - What Distorts the Results of Marketing Research
Englishing
How to write an OPINION ESSAY - Lesson 4: Transition words
In this lesson, Mr. P. will discuss how to write an opinion essay using transition words to create a better flow among paragraphs and sentences. He will focus on four groups of transition words and then changed an essay. This lesson is...
Curated Video
Statistics for Data Science and Business Analysis - Working with Estimators and Estimates
This video explores the estimators and estimates, and differentiates between the two concepts. This clip is from the chapter "Inferential Statistics Fundamentals" of the series "Statistics for Data Science and Business Analysis".This...
Curated Video
Statistics for Data Science and Business Analysis - Correlation and Causation
In this video, you will learn about correlation and causation. This clip is from the chapter "The Fundamentals of Regression Analysis" of the series "Statistics for Data Science and Business Analysis".This section includes fundamentals...
Global Health with Greg Martin
T-test, ANOVA and Chi Squared test made easy.
Statistics doesn't need to be difficult. Using the t-test, ANOVA or Chi Squared test as part of your statistical analysis is straight forward. You do need to understanding the underlying principles of hypothesis testing and p-values of...