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Machine Learning

This class was created by Brainscape user Simon Sardorf. Visit their profile to learn more about the creator.

By: Simon Sardorf
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Decks in this class (12)

Lecture 1: Fundamentals of Statistics: Probability and Distribution
Events are independent when,
How do you calculate the probabil...,
What is conditional probability w...
16  cards
Lecture 2 - Introduction to Machine Learning
What is machine learning,
What are the primary differences ...,
What is an example of a timeline ...
46  cards
Lecture 3 - Unsupervised Machine Learning
What are some examples of unsuper...,
Describe clustering what inputs d...,
Can you give some examples of use...
34  cards
Lecture 4 - Supervised Machine Learning: KNN and Regression
What is k nearest neighbors what ...,
Explain how the knn algorithm works,
How can you choose k
25  cards
Lecture 5 - Dimensionality Reduction - Principal Component Analysis, Linear Discrimination Analysis, Singular Value Decomposition
What is meant by degrees of freedom,
What is dimensionality reduction,
What is the goal of dimensionalit...
25  cards
Lecture 6 - Support Vector Machines, Decision Tree, Ensemble, Hypothesis Testing
Are support vector machines svm u...,
Is svm used for regression or cla...,
How does svm work on nonlinear data
39  cards
Lecture 7 - Outlier Detection, Feature Selection, Similar Items, Recommender Systems, Naive Bayes Classifiers, Class Imbalance
What is an outlier,
What can cause outliers,
True or false you should always t...
45  cards
Lecture 8 - (Stochastic) Gradient Descent, Regularization, Artificial Neural Networks, Perceptron
What is gradient descent,
What is the complexity of gradien...,
Explain the process of gradient d...
53  cards
Lecture 9 - Cloud Computing, Big Data, Tensor-flow, Recurrent Neural Networks, Distributed Deep Learning
What is cloud computing,
What is cloud computing composed of,
What are the five characteristics...
32  cards
Lecture 12: Philosophy and Ethics of AI
What is the difference between we...,
Does strong ai exist,
True or false ai is good in patte...
8  cards
Lecture 10 - LSTM - CNN -GAN - BatchNorm
Lstm stands for,
Lstm is used for,
What are the components of lstm
30  cards
Lecture 11 - Hyper-parameter Optimization - Deep Generative Models - Autoencoders
Why is optimization important,
Standard training method is,
Explain the stochastic gradient t...
32  cards

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Machine Learning

  • Class purpose General learning

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