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.
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This video focuses on AWS step functions.
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This clip is from the chapter "Domain 3: Processing" of the series "AWS Certified Data Analytics Specialty (2022) Hands-on".In this section, we will complete our "order history app"...

This video focuses on AWS Glue DataBrew.
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This clip is from the chapter "Domain 3: Processing" of the series "AWS Certified Data Analytics Specialty (2022) Hands-on".In this section, we will complete our "order history app"...

This video covers AWS data exchange.
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This clip is from the chapter "Everything Else" of the series "AWS Certified Data Analytics Specialty (2022) Hands-on".In this section, you will learn about Amazon Web Services (AWS)...

In this video, we will be discussing data masking control and how it can help protect sensitive information. Data masking is the process of obscuring or hiding certain data elements within a database or application. This can include...

In this video, we will see how we could develop several predictive models for Titanic survival prediction and do some analytics using them. In particular, we will discuss logistic regression, random forest, and linear SVM. We start with...

Polymer properties such as density, melt index, and melt flow rate must be kept within tight specifications for each grade. This case study is to analyze polymer production data to predict melt flow...

From the section: Supervised Learning: Classification. In this section, the author talks about kNN- Classification, Naive Bayes Classification, SVM- Linear and Non-Linear Classification and also Gradient Boosting Machine...

In this video, we will see a type of machine learning process that is supervised learning. We will also see linear regression. We will use it for movie rating prediction. • See the spam filtering example • Use linear regression for movie...

Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine...

Training a classification model to predict the class of an Iris flower.

Implementing a Text Classification project by using Natural Language Processing to understand the sentiment of move reviews

From the section: Regression Task Airbnb Prices in New York. We will use a real-world Airbnb dataset that contains data about New York properties for rent in 2019 on Airbnb, including their price. It is a simple dataset and makes a...

This case study is to determine the factors (inputs) that have correlation to the concrete compressive strength (output).



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upyter Notebook
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Training and testing a regression model to predict the weight of the fish.

This video explains a simple linear regression model.
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This clip is from the chapter "Linear Regression: A Simple Model" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This...

In this video, we will use python to write a simple ensemble learning model for Regression. • We will use Jupyter Notebook to execute our code • Use of Height vs weight to demonstrate the ensemble technique • Use different models instead...

Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine...

Solutions to Problem 3.

This video explains linear regression in R.
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This clip is from the chapter "Linear Regression - a Real Model" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section explains...

Once data is read into Python, a first step is to analyze the data with summary statistics. This is especially true if the data set is large. Summary statistics include the count, mean, standard deviation, maximum,...

From the section: Simple Classification Tree. This section we will expand our knowledge of regression Decision tree to classification trees, we will also learn how to create a classification tree in Python.



Simple...

From the section: Introduction to Artificial Neural Networks (ANN). This section introduces Artificial Neural Networks. You will learn about Neural Network for Binary Classifications, Neural Network with PCA for Binary...

From the section: Predicting Sales with Supervised Learning. In this section, learners will use their first machine learning techniques, including Support Vector Machines and Artificial Neural Networks. These techniques will be...