From the section: Introduction. In this section, the learner will be introduced to the environment and working of Keras and how to set it up to go coding. A very brief introduction along with an illustration will be given to deep...

In this video, the teacher explains how to compare two data sets using comparative box plots. They discuss the elements of a box plot, such as the minimum, maximum, median, lower quartile, upper quartile, and interquartile range. The...

Training and testing a classification model to predict the patient's diabetic status.

Deep learning is currently one of the best providers of solutions regarding problems in image recognition, speech recognition, object recognition, and natural language with its increasing number of libraries that are available in...

Recommendation systems is a subclass of information filtering system that helps predict the "rating" or "preference" based on the rating provided by users of an item. We will also see collaborative filtering and content-based filtering...

Concrete mixtures have several variations. This data set is a case study for data visualization and exploration to predict the concrete compressive strength (MPa).



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26 - ML Draw Classification

For this video, we will be using bank marketing datasets. The data is related to direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. We will do predictive analytics using...

Operational Technology (OT) includes computer systems and equipment that make changes to the physical world. Sensors, actuators, and computer control systems are critical to safe operation and are increasingly under threat...

In this video, the teacher explains how to find the center of data sets using mean and median. They provide examples and equations to calculate both measures of center, and discuss when it is appropriate to use mean or median based on...

This video gives an introduction to exploratory data analysis.
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This clip is from the chapter "Exploratory Data Analysis" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This...

This video demonstrates a practical application of machine learning.
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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...

From the section: Machine Learning: Part 1. In this section, we’ll learn how machine learning works, and how it fits in with the world of AI and deep learning. And learn to train, test and validate the data using K-fold...

This video emphasizes the importance of including titles and labels to clearly communicate the data being represented. The video also addresses common misunderstandings, such as confusing frequencies with data values. Overall, it...

In this video, we will see how to perform a bit more complex predictive analytics using the bag-of-words concept of NLP with TensorFlow. At first, we will formalize the problem, and then will explore the dataset that will be used....

This video explains Tibbles in data frames.
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This clip is from the chapter "Data Types and Structures in R" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This video explains data...

If you want to use R programming to create plots and graphs using the ggplot package, then watch this video. In this video, I'll go though how to visualize two numeric variables and one categoric variable using line graphs and faceting...

In this video I talk about how to understand missing data and missing values. I also provide 5 strategies to deal with missing data using R programming. If you're doing quantitative analysis or statistical analysis, your dataset will...

In this video, we will see Neural factorization machines is used to for making predictions under sparse settings by seamlessly combining the linearity of FM and the non-linearity of the neural network. • Understand neural factorization...

In this video, the concept of range in statistics is explained. The range is a single number that represents the spread of data. It is found by subtracting the smallest number from the largest number in a data set. The video also...

This video explains the different approaches in machine learning.
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This clip is from the chapter "Introduction to Machine Learning" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for...

This video explains hands-on exploratory data analysis.
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This clip is from the chapter "Exploratory Data Analysis" of the series "Data Science and Machine Learning with R from A-Z Course [Updated for 2021]".This section...

R programming is easy. In this video, I'll walk you though how to clean your data; how to manipulate (or wrangle) your data; how to summarize your data; how to create tables and describe your data; how to visualize your data using ggplot...

From the section: Simple Decision trees. In this section, we will start with the basic theory of decision tree then we cover data pre-processing topics like missing value imputation, variable transformation and Test-Train split. In...