Learn Machine Learning
30 videos • 6,283 views • by IntuitiveML
1
What is Machine Learning?
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2
Terms: Training vs. Evaluation vs. Prediction
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3
Terms: Nonlinearity
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4
Neural Network Caveats
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5
Types of Machine Learning
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6
Intuition: Perceptrons and Artificial Neural Networks
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7
Intuition: Artificial Neural Networks
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8
What is the difference between a Deep Neural Network and an Artificial Neural Network?
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9
Terms: Activation Functions
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10
Intuition: How does the Heaviside Activation Function work?
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11
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12
What is a Confusion Matrix? How does it work? Why do we care? (Fixing last week's mistake!)
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13
Loss functions: What are they?
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14
Classification Vs. Regression in one minute.
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15
Intuition: Training Set vs. Test Set vs. Validation Set
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16
Intuition Behind Linear Regression
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17
What is independence (probability)?
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18
Terms: Independent and Identically Distributed (IID)
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19
What is overfitting?
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20
What is an RNN?
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21
Recurrent Neural Network Implementation Details
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22
Intuition of Likelihood in Machine Learning
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23
Maximum Likelihood Estimation (MLE): The Intuition
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24
Intuition: Ensemble Learning | Ensembles in Machine Learning #1
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25
Bagging... works how? | Ensembles #2: Intuition of Bootstrap Aggregating in Machine Learning
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26
Boosting in Machine Learning | Ensembles #3
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27
How Convolutional Neural Networks Work | CNN's #1
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28
What is a receptive field? | CNNs #2
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29
What is pooling? | CNN's #3
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30
I get confused trying to learn Gaussian Processes | Learn with me!
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