Image Understanding: Instructional Materials


Learn Python AI for Image Recognition & Fraud Detection

#artificialintelligence

Combine Python & TensorFlow powers to build projects. In this course, you will learn how to code in Python, calculate linear regression with TensorFlow, and use AI for automation. Together with a professional you will perform CIFAR 10 image data and recognition and analyze credit card fraud by building practical projects. We explain everything in a straightforward teaching style that is easy to understand. Join Mammoth Interactive in this course, where we blend theoretical knowledge with hands-on coding projects to teach you everything you need to know as a beginner to credit card fraud detection What you'll learn Learn how to code in Python, a popular coding language used for websites like YouTube and Instagram.


Python Image Recognition: Hands-On Data Science Course

#artificialintelligence

Python image recognition sounds exciting, right? However, it can also seem a bit intimidating. There's no need to be scared! This tutorial will teach you Python basics and how to use TensorFlow. Take this chance to discover how to code in Python and learn TensorFlow linear regression then apply these principles to automated Python image recognition.


Learn Python AI for Image Recognition & Fraud Detection

@machinelearnbot

A wildly successful Kickstarter funded this Mammoth Interactive course. "It's simple and relaxing-- just what the doctor ordered." Enroll now to learn in-demand skills that employers are seeking. Data scientists make an average of $120,000 annually. With this course we will help get you there!


Image Recognition TensorFlow

#artificialintelligence

Our brains make vision seem easy. It doesn't take any effort for humans to tell apart a lion and a jaguar, read a sign, or recognize a human's face. But these are actually hard problems to solve with a computer: they only seem easy because our brains are incredibly good at understanding images. In the last few years, the field of machine learning has made tremendous progress on addressing these difficult problems. In particular, we've found that a kind of model called a deep convolutional neural network can achieve reasonable performance on hard visual recognition tasks -- matching or exceeding human performance in some domains.