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[FreeTutorials Us] Udemy - Projects in Machine Learning Beginner To Professional
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Name:[FreeTutorials Us] Udemy - Projects in Machine Learning Beginner To Professional
Infohash: E0A4B5BB7CF93C587232ECBEC3C28D795973A69F
Total Size: 4.24 GB
Magnet: Magnet Download
Seeds: 3
Leechers: 1
Stream: Watch Full Movies @ LimeMovies
Last Updated: 2026-01-07 12:25:25 (Update Now)
Torrent added: 2018-10-19 22:07:21
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Torrent Files List
10. Project 5 Object Recognition (Size: 4.24 GB) (Files: 144)
10. Project 5 Object Recognition
1.1 Object Recognition.zip.zip
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.zip.zip
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.zip.zip
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.zip.zip
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.zip.zip
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
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
2. Supervised Learning - part 1
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
7.1 Supervised Learning.zip.zip
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
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
5.1 Unsupervised Learning.zip.zip
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
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
6. Warmup Project
1.1 Final Project.zip.zip
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.zip.zip
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.zip.zip
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
9. Project 4 Intro to Natural Language Processing
1.1 Intro to Natural Language Processing.zip.zip
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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