AI News, Machine Learning Foundations: A Case Study Approach

Machine Learning Foundations: A Case Study Approach

At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images.

Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This

Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output.

In subsequent courses, you will delve into the components of this black box by examining models and algorithms.

Lecture 3 | Loss Functions and Optimization

Lecture 3 continues our discussion of linear classifiers. We introduce the idea of a loss function to quantify our unhappiness with a model's predictions, and ...

Lecture 14 | Deep Reinforcement Learning

In Lecture 14 we move from supervised learning to reinforcement learning (RL), in which an agent must learn to interact with an environment in order to ...

Machine Learning Tutorial For Beginners | Machine Learning Course - Introduction | Simplilearn

This Machine Learning Tutorial will give a brief introduction to Machine Learning and discusses how this is useful to us using real-life examples. At the end of ...

Intro to Azure ML: Building a Machine Learning Model

Let's build our first machine learning model in Azure ML. First, we have to go shopping for a machine learning model. We must identify what type of machine ...

Lecture 16 | Adversarial Examples and Adversarial Training

In Lecture 16, guest lecturer Ian Goodfellow discusses adversarial examples in deep learning. We discuss why deep networks and other machine learning ...

A Guide to CoreML on iOS

Apple's newly released CoreML framework makes it super simple for developers to run inference of pre-trained models on their iOS devices. Let's talk about ...

3.1: Introduction to Session 3 - What is Machine Learning?

This video is the introduction to Session 3 of the ITP "Intelligence and Learning" course ...

Introducing ML.NET : Build 2018

ML.NET is aimed at providing a first class experience for Machine Learning in .NET. Using ML.NET, .NET developers can develop and infuse custom AI into ...

Lecture 7 | Training Neural Networks II

Lecture 7 continues our discussion of practical issues for training neural networks. We discuss different update rules commonly used to optimize neural networks ...

Lecture 01 - The Learning Problem

The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's ...