Curated Video
Discuss the importance of data : The Data set for Classification problem
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 Classification Tree:...
Curated Video
Describe a neural network : Neural Network for Regression
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 Classifications,...
Packt
Define artificial intelligence : AI, Machine Learning, Deep Learning Overview
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...
Packt
Develop an AI system to solve a real-world problem : Building Artificial Neural Networks
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 applied...
Curated Video
Comparing Data Sets Using Comparative Box Plots
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...
Curated Video
Deep Learning with Python (Video 12)
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 Python....
Fun Robotics
Diabetes Classification Model
Training and testing a classification model to predict the patient's diabetic status.
Curated Video
Predictive Analytics with TensorFlow 10.1: Recommendation Systems
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...
APMonitor
Visualization Case Study: Concrete Strength
Concrete mixtures have several variations. This data set is a case study for data visualization and exploration to predict the concrete compressive strength (MPa). 0:00 Introduction 0:20 Concrete Case Study 1:52 Jupyter Notebook Source...
Curated Video
Predictive Analytics with TensorFlow 7.3:Using Multilayer Perceptrons for Predictive Analytics
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...
APMonitor
Machine Learning IOT/OT Cybersecurity
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 of attack....
Curated Video
Finding the Center of Data Sets: Mean and Median
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...
Curated Video
Data Science and Machine Learning with R - Exploratory Data Analysis Introduction
This video gives an introduction to exploratory data analysis. 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 explains...
Curated Video
Data Science and Machine Learning with R - A Simple Model
This video demonstrates a practical application of machine learning. 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...
Curated Video
Create a computer vision system using decision tree algorithms to solve a real-world problem : [Activity] Decision Trees In Action
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 cross-validation....
Curated Video
Graphically Representing Data with Dot Plots
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...
Curated Video
Predictive Analytics with TensorFlow 6.3: Using BOW for Predictive Analytics
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....
Curated Video
Data Science and Machine Learning with R - Data Frames: Tibbles
This video explains Tibbles in data frames. 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 types and...
R Programming 101
How to draw a line graph using ggplot with R programming. Plots and graphs to visualize 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...
Global Health with Greg Martin
Understanding missing data and missing values. 5 ways to deal with missing data using R programming
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...
Curated Video
Predictive Analytics with TensorFlow 10.3: Improved Factorization Machines for Predictive Analytics
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...
Curated Video
Understanding and Describing Data Distribution with Range
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...
Curated Video
Data Science and Machine Learning with R - Introduction to Machine Learning Part Two
This video explains the different approaches in machine learning. 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 2021]".This section...