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Artificial Intelligence Course | Intellipaat
In this Artificial Intelligence tutorial for beginners video you will learn all the major basic concepts in Artificial Intelligence like what is ai, difference between ai, ml and dl, topology of a neural network, how to train network with backpropagation with an in depth demo on tensorflow and keras.
Data Science for Beginners (Youtube)
Data Science tutorial will help you learn what is Data Science and master the foundations of data science, data sourcing, coding, mathematics, and statistics. In this complete Data Science courses video, you will get to understand the concepts of Data Science like Supervised Learning which includes data manipulation, Data Visualization, Linear Regression, Logistic Regression, Decision Tree, Random Forest. You will also learn about Unsupervised Learning which includes k-means clustering, user-based & item-based filtering, association rule mining, etc among others.
Machine Learning Tutorial | Intellipaat
This machine learning tutorial covers what is machine learning, machine learning algorithms like linear regression, binary classification, decision tree, random forest and unsupervised algorithm like k means clustering in detail with complete hands on demo. There is machine learning complete project and machine learning interview questions as well in this machine learning full course video to prepare you for the job interview.
Data Visualization 101
This online data visualization course will teach you how to identify all the factors that go into a successful visualization: thinking like your audience, finding the right chart for your data, and uncovering what the data really says. Along the way, you'll learn all about the most common chart types. You'll also learn the basics of R, one of the most in-demand programming languages.
Podcast.__init__
Since its beginning in March of 2014 Podcast.__init__ has brought you stories of the people that make the Python community great. Every week a new episode provides useful and informative insights into the projects, platforms, and practices that engineers, business leaders, and data scientists need to know about to learn and grow in their career.