Introduction to Machine Learning
Where to Watch Introduction to Machine Learning
25.
Mastering the Machine Learning Process
2020-11-06
Finish the series with a lightning tour of meta-learning: algorithms that learn how to learn, making it possible to solve problems that are otherwise unmanageable. Examine two approaches: one that reasons about discrete problems using satisfiability solvers and another that allows programmers to optimize continuous models.
Watch Introduction to Machine Learning Season 1 Episode 25 Now
24.
Protecting Privacy within Machine Learning
2020-11-06
Machine learning is both a cause and a cure for privacy concerns. Hear about two notorious cases where de-identified data was unmasked.
Watch Introduction to Machine Learning Season 1 Episode 24 Now
23.
The Unexpected Power of Over-Parameterization
2020-11-06
Probe the deep-learning revolution that took place around 2015, conquering worries about overfitting data due to the use of too many parameters. Dr.
Watch Introduction to Machine Learning Season 1 Episode 23 Now
22.
Causal Inference Comes to Machine Learning
2020-11-06
Get acquainted with a powerful new tool in machine learning, causal inference, which addresses a key limitation of classical methods: the focus on correlation to the exclusion of causation. Practice with a historic problem of causation: the link between cigarette smoking and cancer, which will always be obscured by confounding factors.
Watch Introduction to Machine Learning Season 1 Episode 22 Now
21.
Inverse Reinforcement Learning from People
2020-11-06
Are you no good at programming? Machine learning can a give a demonstration, predict what you want, and suggest improvements.
Watch Introduction to Machine Learning Season 1 Episode 21 Now
20.
Deep Learning for Speech Recognition
2020-11-06
Consider the problem of speech recognition and the quest, starting in the 1950s, to program computers for this task. Then, delve into algorithms that machine learning uses to create today's sophisticated speech recognition systems.
Watch Introduction to Machine Learning Season 1 Episode 20 Now
19.
Making Photorealistic Images with GANs
2020-11-06
A new approach to image generation and discrimination pits both processes against each other in a generative adversarial network, or GAN. The technique can produce a new image based on a reference class, for example making a person look older or younger, or automatically filling in a landscape after a building has been removed.
Watch Introduction to Machine Learning Season 1 Episode 19 Now
18.
Making Stylistic Images with Deep Networks
2020-11-06
One way to think about the creative process is as a two-stage operation, involving an idea generator and a discriminator. Study two approaches to image generation using machine learning.
Watch Introduction to Machine Learning Season 1 Episode 18 Now
17.
Deep Networks That Output Language
2020-11-06
Continue your study of machine learning and language by seeing how computers not only read text, but how they can also generate it. Explore the current state of machine translation, which rivals the skill of human translators.
Watch Introduction to Machine Learning Season 1 Episode 17 Now
16.
Text Categorization with Words as Vectors
2020-11-06
Previously, you saw how machine learning is used in spam filtering. Dig deeper into problems of language processing, such as how a computer guesses the word you are typing and possibly even badly misspelling.
Watch Introduction to Machine Learning Season 1 Episode 16 Now
15.
Getting a Deep Learner Back on Track
2020-11-06
Roll up your sleeves and debug a deep-learning program. The software is a neural net classifier designed to separate pictures of animals and bugs.
Watch Introduction to Machine Learning Season 1 Episode 15 Now
14.
Deep Learning for Computer Vision
2020-11-06
Discover how the ImageNet challenge helped revive the field of neural networks through a technique called deep learning, which is ideal for tasks such as computer vision. Consider the problem of image recognition and the steps deep learning takes to solve it.
Watch Introduction to Machine Learning Season 1 Episode 14 Now
13.
Games with Reinforcement Learning
2020-11-06
In 1959, computer pioneer Arthur Samuel popularized the term machine learning for his checkers-playing program. Delve into strategies for the board game Othello as you investigate today's sophisticated algorithms for improving play, at least for the machine.
Watch Introduction to Machine Learning Season 1 Episode 13 Now
12.
Recommendations with Three Types of Learning
2020-11-06
Recommender systems are ubiquitous, from book and movie tips to work aids for professionals. But how do they function?
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11.
Clustering and Semi-Supervised Learning
2020-11-06
See how a combination of labeled and unlabeled examples can be exploited in machine learning, specifically by using clustering to learn about the data before making use of the labeled examples.
Watch Introduction to Machine Learning Season 1 Episode 11 Now
10.
Pitfalls in Applying Machine Learning
2020-11-06
Explore pitfalls that loom when applying machine learning algorithms to real-life problems. For example, see how survival statistics from a boating disaster can lead to false conclusions.
Watch Introduction to Machine Learning Season 1 Episode 10 Now
9.
The Fundamental Pitfall of Overfitting
2020-11-06
Having covered the five fundamental classes of machine learning in the previous episodes, now focus on a risk common to all: overfitting. This is the tendency to model training data too well, which can harm the performance on the test data.
Watch Introduction to Machine Learning Season 1 Episode 9 Now
8.
Nearest Neighbors for Using Similarity
2020-11-06
Simple to use and speedy to execute, the nearest neighbor algorithm works on the principle that adjacent elements in a dataset are likely to share similar characteristics. Try out this strategy for determining a comfortable combination of temperature and humidity in a house.
Watch Introduction to Machine Learning Season 1 Episode 8 Now
7.
Genetic Algorithms for Evolved Rules
2020-11-06
When you encounter a new type of problem and don't yet know the best machine learning strategy to solve it, a ready first approach is a genetic algorithm. These programs apply the principles of evolution to artificial intelligence, employing natural selection over many generations to optimize your results.
Watch Introduction to Machine Learning Season 1 Episode 7 Now
6.
Bayesian Models for Probability Prediction
2020-11-06
A program need not understand the content of an email to know with high probability that it's spam. Discover how machine learning does so with the Naive Bayes approach, which is a simplified application of Bayes' theorem to a simplified model of language generation.
Watch Introduction to Machine Learning Season 1 Episode 6 Now
5.
Opening the Black Box of a Neural Network
2020-11-06
Take a deeper dive into neural networks by working through a simple algorithm implemented in Python. Return to the green-screen problem from the first episode to build a learning algorithm that places the professor against a new backdrop.
Watch Introduction to Machine Learning Season 1 Episode 5 Now
4.
Neural Networks for Perceptual Rules
2020-11-06
Graduate to a more difficult class of problems: learning from images and auditory information. Here, it makes sense to address the task more or less the way the brain does, using a form of computation called a neural network.
Watch Introduction to Machine Learning Season 1 Episode 4 Now
3.
Decision Trees for Logical Rules
2020-11-06
Can machine learning beat a rhyming rule, taught in elementary school, for determining whether a word is spelled with an I-E or an E-I-as in diet and weigh? Discover that a decision tree is a convenient tool for approaching this problem.
Watch Introduction to Machine Learning Season 1 Episode 3 Now
2.
Starting with Python Notebooks and Colab
2020-11-06
The demonstrations in this series use the Python programming language, the most popular and widely supported language in machine learning. Dr.
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1.
Telling the Computer What We Want
2020-11-06
This series teaches you about machine-learning programs and how to write them in the Python programming language. For those new to Python, a get-started tutorial is included.
Watch Introduction to Machine Learning Season 1 Episode 1 Now
Introduction to Machine Learning is a series categorized as a new series. Spanning 1 seasons with a total of 25 episodes, the show debuted on 2020. The series has earned a no reviews from both critics and viewers. The IMDb score stands at undefined.
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