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[FreeTutorials Eu] [UDEMY] Projects in Machine Learning Beginner To Professional - FTU]
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10. Project 5 Object Recognition (Size: 4.24 GB) (Files: 173)
10. Project 5 Object Recognition
1.1 Object Recognition
Object Recognition
Object Recognition (HTML Notebook).html
Object Recognition (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Loading and Preprocessing the CIFAR10 Dataset.mp4
2. Loading and Preprocessing the CIFAR10 Dataset.srt
3. Building and Deploying the All-CNN Network Part 1.mp4
3. Building and Deploying the All-CNN Network Part 1.srt
4. Building and Deploying the All-CNN Network Part 2.mp4
4. Building and Deploying the All-CNN Network Part 2.srt
11. Project 6 Image Super Resolution
1.1 Image Super Resolution
results
baboon.png
baby_GT.png
barbara.png
bird_GT.png
butterfly_GT.png
coastguard.png
comic.png
face.png
flowers.png
foreman.png
head_GT.png
lenna.png
monarch.png
pepper.png
ppt3.png
woman_GT.png
zebra.png
Image Super Resolution with the SRCNN (HTML Notebook).html
Image Super Resolution with the SRCNN (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Quality Metrics and Preprocessing Images.mp4
2. Quality Metrics and Preprocessing Images.srt
3. Image Super Resolution using Deep Learning.mp4
3. Image Super Resolution using Deep Learning.srt
12. Project 7 Text Classification
1.1 Text Classification
Text Classification
NLP for Text Classification (HTML).html
NLP for Text Classification (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Feature Engineering.mp4
2. Feature Engineering.srt
3. Deploying Sklearn Classifiers.mp4
3. Deploying Sklearn Classifiers.srt
13. Project 8 - KMeans
1.1 KMeans
KMeans
KMeans Clustering for Imagery Analysis (HTML).html
KMeans Clustering for Imagery Analysis (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Preprocessing Images for Clustering.mp4
2. Preprocessing Images for Clustering.srt
3. Evaluation and Visualization.mp4
3. Evaluation and Visualization.srt
14. Project 9 PCA
1.1 PCA
PCA
PCA Compression and Visualization (HTML).html
PCA Compression and Visualization (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. The Elbow Method.mp4
2. The Elbow Method.srt
3. PCA Compression and Visualization.mp4
3. PCA Compression and Visualization.srt
2. Supervised Learning - part 1
7.1 Supervised Learning
Supervised Learning
Unit 2 Project - Supervised Learning in Python (HTML Document).html
Unit 2 Project - Supervised Learning in Python (Jupyter Notebook).ipynb
10.1 Unit 2 Solutions.pdf.pdf
10. Quiz- Answers - Section 2.html
1. Introduction to Supervised Learning.mp4
1. Introduction to Supervised Learning.srt
2. Linear Methods for Classification.mp4
2. Linear Methods for Classification.srt
3. Linear Methods for Regression.mp4
3. Linear Methods for Regression.srt
4. Support Vector Machines.mp4
4. Support Vector Machines.srt
5. Basis Expansions.mp4
5. Basis Expansions.srt
6. Model Selection Procedures.mp4
6. Model Selection Procedures.srt
7. Bonus! Supervised Learning Project in Python Part 1.mp4
7. Bonus! Supervised Learning Project in Python Part 1.srt
8. Bonus! Supervised Learning Project in Python Part 2.mp4
8. Bonus! Supervised Learning Project in Python Part 2.srt
9.1 Unit 2 Quiz.pdf.pdf
9. Quiz- Questions- Section 2.html
3. Unsupervised Learning
5.1 Unsupervised Learning
Unsupervised Learning
Unit 3 Project - KMeans Clustering (HTML).html
Unit 3 Project - KMeans Clustering (Jupyter Notebook).ipynb
1. Introduction to Unsupervised Learning.mp4
1. Introduction to Unsupervised Learning.srt
2. Association Rules.mp4
2. Association Rules.srt
3. Cluster Analysis.mp4
3. Cluster Analysis.srt
4. Reinforcement Learning.mp4
4. Reinforcement Learning.srt
5. Bonus! KMeans Clustering Project.mp4
5. Bonus! KMeans Clustering Project.srt
6.1 Unit 3 Quiz.pdf.pdf
6. Quiz- Questions- Section 3.html
7.1 Unit 3 Solutions.pdf.pdf
7. Quiz- Answers - Section 3.html
6. Warmup Project
1.1 Final Project
Final Project
Final Project (HTML).html
Final Project (Jupyter Notebook).ipynb
1. Setting up OpenAI Gym.mp4
1. Setting up OpenAI Gym.srt
2. Building and Training the Network Part 1.mp4
2. Building and Training the Network Part 1.srt
3. Building and Training the Network Part 2.mp4
3. Building and Training the Network Part 2.srt
7. Project 1Board Game Review Prediction
1.1 Board Game Review Predictions
Board Game Review Predictions
Board Game Review Prediction (HTML).html
Board Game Review Prediction (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Board Game Review Prediction - Building the Dataset Part 1.mp4
2. Board Game Review Prediction - Building the Dataset Part 1.srt
3. Board Game Review Prediction - Building the Dataset Part 2.mp4
3. Board Game Review Prediction - Building the Dataset Part 2.srt
4. Board Game Review Prediction - Training the Models.mp4
4. Board Game Review Prediction - Training the Models.srt
8. Project 2 Credit Card Fraud Detection
1.1 Credit Card Fraud Detection
Credit Card Fraud Detection
Credit Card Fraud Detection (HTML).html
Credit Card Fraud Detection (Jupyter Notebook).ipynb
1. Intro.mp4
1. Intro.srt
2. Credit Card Fraud Detection - The Dataset.mp4
2. Credit Card Fraud Detection - The Dataset.srt
3. Credit Card Fraud Detection - The Algorithms.mp4
3. Credit Card Fraud Detection - The Algorithms.srt
1. An Introduction to Machine Learning
1. Introduction.mp4
1. Introduction.srt
2. What is Machine Learning.mp4
2. What is Machine Learning.srt
3. Types and Applications of ML.mp4
3. Types and Applications of ML.srt
4. AI vs ML.mp4
4. AI vs ML.srt
5. Essential Math for ML and AI.mp4
5. Essential Math for ML and AI.srt
6.1 Unit 1 Quiz.pdf.pdf
6. Quiz- Questions- Section1.html
7.1 Unit 1 Solutions.pdf.pdf
7. Quiz- Answers - Section 1.html
4. Neural Networks
1. Introduction to Neural Networks.mp4
1. Introduction to Neural Networks.srt
2. The Perceptron.mp4
2. The Perceptron.srt
3. The Backpropagation Algorithm.mp4
3. The Backpropagation Algorithm.srt
4. Training Procedures.mp4
4. Training Procedures.srt
5. Convolutional Neural Networks.mp4
5. Convolutional Neural Networks.srt
5. Real World Machine Learning
1. Introduction to Real World ML.mp4
1. Introduction to Real World ML.srt
2. Choosing an Algorithm.mp4
2. Choosing an Algorithm.srt
3. Design and Analysis of ML Experiments.mp4
3. Design and Analysis of ML Experiments.srt
4. Common Software for ML.mp4
4. Common Software for ML.srt
5.1 Unit 5 Quiz.pdf.pdf
5. Quiz- Questions- Section 5.html
6.1 Unit 5 Solutions.pdf.pdf
6. Quiz- Answers - Section 5.html
9. Project 4 Intro to Natural Language Processing
1. Intro.mp4
1. Intro.srt
2. Tokenizing, Stop Words, and Stemming.mp4
2. Tokenizing, Stop Words, and Stemming.srt
3. Tagging, Chunking, and Named Entity Recognition.mp4
3. Tagging, Chunking, and Named Entity Recognition.srt
4. Text Classification.mp4
4. Text Classification.srt
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