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Advanced-lane-finding

Advanced Lane Finding Videos

1 – Welcome

2 – Overview_(new)

3 – Getting Started, Camera Calibration

4 – Distortion

5 – Pinhole Camera Model and Types of Distortion

6 – Distortion

7 – Chessboards

8 – Lane Curvature

9 – Perspective Transform_(new)

10 – Transforming a Stop Sign

11 – Gradient Threshold

12 – Color Spaces

13 – Color Spaces and Thresholding

14 – Project Steps

15 – Finding Lane Pixels by Histogram and Sliding Window_(new)

16 – Onward!

Advanced Lane Finding Subtitles

Behavoir cloning

Behavioral Cloning Subtitles

Behavioral Cloning Videos

simulator-linux

simulator-macos

simulator-windows-64

Convolutional neural network

cnn (1)

cnn (2)

cnn (3)

cnn (4)

cnn (5)

cnn

Decision Tree

Decision Trees Subtitles

Decision Trees Videos

Deep neural network

Convolutional Neural Networks Videos

Deep Neural Networks Videos

multilayer-perceptron (1)

multilayer-perceptron (2)

multilayer-perceptron (3)

multilayer-perceptron

Finding-lane-lines

Finding Lane Lines Subtitles

Finding Lane Lines Videos

Introduction to nerual-network

Introduction to Neural Networks Subtitles

Introduction to Neural Networks Videos

Introduction to tensorflow

Introduction to TensorFlow Subtitles

Introduction to TensorFlow Videos

keras

Keras Subtitles

Keras Videos

Machine learning

Machine Learning and Stanley Videos

1 – Intro to Classifiers_(new)

2 – ML in The Google Self-Driving Car_(new)

3 – Intro To Stanley Terrain Classification

4 – Stanley Terrain Classification

5 – Speed Scatterplot_ Grade and Bumpiness

6 – Speed Scatterplot_ Grade and Bumpiness Solution

7 – Speed Scatterplot 2

8 – Speed Scatterplot 2 Solution

9 – Speed Scatterplot 3

10 – Speed Scatterplot 3 Solution

11 – From Scatterplots to Predictions_(new)

12 – From Scatterplots to Predictions Solution_(new)

13 – From Scatterplots to Predictions 2

14 – From Scatterplots to Predictions 2 Solution

15 – From Scatterplots to Decision Surfaces

16 – From Scatterplots to Decision Surfaces Solution

17 – A Good Linear Decision Surface

18 – A Good Linear Decision Surface Solution

19 – Transition to Using Naive Bayes

20 – NB Decision Boundary in Python

21 – Getting Started With sklearn

22 – Gaussian NB Example

23 – GaussianNB Deployment on Terrain Data

24 – GaussianNB Deployment on Terrain Data Solution

25 – Calculating NB Accuracy

26 – Calculating NB Accuracy Solution

27 – Training and Testing Data

28 – Naive Bayes Strengths and Weaknesses

29 – Congrats on Learning Naive Bayes_(new)

Lesson 1–Naive Bayes Subtitles

Miniflow

MiniFlow Subtitles

MiniFlow Videos

mnist.pkl

support vector machine

Lesson 2–SVM Subtitles

Support Vector Machines Videos

The end

The End Videos

Traffice sign classifier

Traffic Sign Classifier Subtitles

Traffic Sign Classifier Videos

traffic-signs-data

Transfer learning

inception-cifar10-bottleneck-data

inception-traffic-bottleneck-data

resnet-cifar10-bottleneck-data

resnet-traffic-bottleneck-data

Transfer Learning Subtitles

Transfer Learning Videos

vgg-cifar10-bottleneck-data

vgg-traffic-bottleneck-data

vehicle detection

Vehicle Detection and Tracking Videos

1 – Intro to Vehicle Tracking_(new)

2 – Intro to Arpan and Drew_(new)

3 – Object Detection Overview

4 – Features

5 – Color Features

6 – Color Histogram Features

7 – Color Spaces_(new)

8 – Gradient Features

9 – HOG Features

10 – Combining Features

11 – Build a Classifier

12 – Labeled Data

13 – Train a Classifier

14 – Sliding Windows

15 – Multi-scale Windows_(new)

16 – Tracking Issues

17 – False Positives

18 – Tracking in Video

19 – Tracking Intuitions

20 – Tracking Pipeline

21 – Summary of Vehicle Detection and Tracking

22 – Traditional vs. Deep Learning Approach_(new)

Vehicle Detection and Tracking Subtitles

welcome

1 – Welcome

2 – Meet Your Instructors

3 – Overview

4 – Career Support

5 – The Great Robot Race

Welcome Subtitles

Welcome Videos