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Practical Machine Learning Tutorial with Python Intro p.1
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Regression Intro - Practical Machine Learning Tutorial with Python p.2
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Regression Features and Labels - Practical Machine Learning Tutorial with Python p.3
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Regression Training and Testing - Practical Machine Learning Tutorial with Python p.4
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Regression forecasting and predicting - Practical Machine Learning Tutorial with Python p.5
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Pickling and Scaling - Practical Machine Learning Tutorial with Python p.6
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Regression How it Works - Practical Machine Learning Tutorial with Python p.7
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How to program the Best Fit Slope - Practical Machine Learning Tutorial with Python p.8
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How to program the Best Fit Line - Practical Machine Learning Tutorial with Python p.9
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R Squared Theory - Practical Machine Learning Tutorial with Python p.10
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Programming R Squared - Practical Machine Learning Tutorial with Python p.11
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Testing Assumptions - Practical Machine Learning Tutorial with Python p.12
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Classification w/ K Nearest Neighbors Intro - Practical Machine Learning Tutorial with Python p.13
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K Nearest Neighbors Application - Practical Machine Learning Tutorial with Python p.14
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Euclidean Distance - Practical Machine Learning Tutorial with Python p.15
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Creating Our K Nearest Neighbors Algorithm - Practical Machine Learning with Python p.16
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Writing our own K Nearest Neighbors in Code - Practical Machine Learning Tutorial with Python p.17
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Applying our K Nearest Neighbors Algorithm - Practical Machine Learning Tutorial with Python p.18
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Final thoughts on K Nearest Neighbors - Practical Machine Learning Tutorial with Python p.19
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Support Vector Machine Intro and Application - Practical Machine Learning Tutorial with Python p.20
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Understanding Vectors - Practical Machine Learning Tutorial with Python p.21
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Support Vector Assertion - Practical Machine Learning Tutorial with Python p.22
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Support Vector Machine Fundamentals - Practical Machine Learning Tutorial with Python p.23
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Support Vector Machine Optimization - Practical Machine Learning Tutorial with Python p.24
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Creating an SVM from scratch - Practical Machine Learning Tutorial with Python p.25
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SVM Training - Practical Machine Learning Tutorial with Python p.26
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SVM Optimization - Practical Machine Learning Tutorial with Python p.27
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Completing SVM from Scratch - Practical Machine Learning Tutorial with Python p.28
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Kernels Introduction - Practical Machine Learning Tutorial with Python p.29
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Why Kernels - Practical Machine Learning Tutorial with Python p.30
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Soft Margin SVM - Practical Machine Learning Tutorial with Python p.31
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Soft Margin SVM and Kernels with CVXOPT - Practical Machine Learning Tutorial with Python p.32
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SVM Parameters - Practical Machine Learning Tutorial with Python p.33
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Clustering Introduction - Practical Machine Learning Tutorial with Python p.34
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Handling Non-Numeric Data - Practical Machine Learning Tutorial with Python p.35
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K Means with Titanic Dataset - Practical Machine Learning Tutorial with Python p.36
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Custom K Means - Practical Machine Learning Tutorial with Python p.37
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K Means from Scratch - Practical Machine Learning Tutorial with Python p.38
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Mean Shift Intro - Practical Machine Learning Tutorial with Python p.39
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Mean Shift with Titanic Dataset - Practical Machine Learning Tutorial with Python p.40
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Mean Shift from Scratch - Practical Machine Learning Tutorial with Python p.41
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Mean Shift Dynamic Bandwidth - Practical Machine Learning Tutorial with Python p.42
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Deep Learning with Neural Networks and TensorFlow Introduction
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Installing TensorFlow (OPTIONAL) - Deep Learning with Neural Networks and TensorFlow p2.1
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TensorFlow Basics - Deep Learning with Neural Networks p. 2
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Neural Network Model - Deep Learning with Neural Networks and TensorFlow
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Running our Network - Deep Learning with Neural Networks and TensorFlow
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Processing our own Data - Deep Learning with Neural Networks and TensorFlow part 5
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Preprocessing cont'd - Deep Learning with Neural Networks and TensorFlow part 6
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Training/Testing on our Data - Deep Learning with Neural Networks and TensorFlow part 7
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Using More Data - Deep Learning with Neural Networks and TensorFlow part 8
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Installing the GPU version of TensorFlow for making use of your CUDA GPU
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Installing CPU and GPU TensorFlow on Windows
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Recurrent Neural Networks (RNN) - Deep Learning with Neural Networks and TensorFlow 10
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RNN Example in Tensorflow - Deep Learning with Neural Networks 11
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Convolutional Neural Networks Basics - Deep Learning withTensorFlow 12
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Convolutional Neural Networks with TensorFlow - Deep Learning with Neural Networks 13
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TFLearn - Deep Learning with Neural Networks and TensorFlow p. 14
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Intro - Training a neural network to play a game with TensorFlow and Open AI
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Training Data - Training a neural network to play a game with TensorFlow and Open AI p.2
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Training Model - Training a neural network to play a game with TensorFlow and Open AI p.3
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Testing Network - Training a neural network to play a game with TensorFlow and Open AI p.4
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Intro and preprocessing - Using Convolutional Neural Network to Identify Dogs vs Cats p. 1
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Building the Network - Using Convolutional Neural Network to Identify Dogs vs Cats p. 2
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Training - Using Convolutional Neural Network to Identify Dogs vs Cats p. 3
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Using our Network - Using Convolutional Neural Network to Identify Dogs vs Cats p. 4
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Introduction - 3D Convolutional Neural Network w/ Kaggle Lung Cancer Detection Competiton p.1
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Reading Files - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.2
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Visualizing - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.3
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Resizing Data - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.4
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Preprocessing data - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.5
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Running the Network - 3D Convolutional Neural Network w/ Kaggle and 3D medical imaging p.6
Description:
Dive into a comprehensive 19-hour tutorial series on machine learning with Python. Learn regression techniques, K-Nearest Neighbors, Support Vector Machines, clustering methods, and deep learning with neural networks. Explore practical applications using TensorFlow, including recurrent and convolutional neural networks. Gain hands-on experience by building models from scratch, working with real-world datasets like Titanic, and tackling advanced projects such as training a neural network to play games and identifying dogs vs cats using CNNs. Conclude with an in-depth look at 3D Convolutional Neural Networks applied to medical imaging in a Kaggle lung cancer detection competition.
Machine Learning with Python
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#Computer Science
#Machine Learning
#Deep Learning
#Programming
#Programming Languages
#Python
#Classification
#Clustering
#K-means
#K-Nearest Neighbors
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