Udemy - Projects in Machine Learning : Beginner To Professional [TP]

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[Tutorialsplanet.NET] Udemy -Projects in Machine Learning Beginner To Professional 1. An Introduction to Machine Learning
  • 1. Introduction.mp4 (1.7 MB)
  • 1. Introduction.srt (1.6 KB)
  • 2. What is Machine Learning.mp4 (29.2 MB)
  • 2. What is Machine Learning.srt (15.8 KB)
  • 3. Types and Applications of ML.mp4 (53.1 MB)
  • 3. Types and Applications of ML.srt (34.8 KB)
  • 4. AI vs ML.mp4 (22.9 MB)
  • 4. AI vs ML.srt (12.5 KB)
  • 5. Essential Math for ML and AI.mp4 (35.8 MB)
  • 5. Essential Math for ML and AI.srt (23.3 KB)
  • 6. Quiz- Questions- Section1.html (0.1 KB)
  • 6.1 Unit 1 Quiz.pdf.pdf (64.5 KB)
  • 7. Quiz- Answers - Section 1.html (0.1 KB)
  • 7.1 Unit 1 Solutions.pdf.pdf (61.7 KB)
10. Project 5 Object Recognition
  • 1. Intro.mp4 (7.2 MB)
  • 1. Intro.srt (1.7 KB)
  • 1.1 Object Recognition.zip.zip (219.0 KB)
  • 2. Loading and Preprocessing the CIFAR10 Dataset.mp4 (180.5 MB)
  • 2. Loading and Preprocessing the CIFAR10 Dataset.srt (32.6 KB)
  • 3. Building and Deploying the All-CNN Network Part 1.mp4 (205.6 MB)
  • 3. Building and Deploying the All-CNN Network Part 1.srt (30.7 KB)
  • 4. Building and Deploying the All-CNN Network Part 2.mp4 (170.8 MB)
  • 4. Building and Deploying the All-CNN Network Part 2.srt (25.3 KB)
11. Project 6 Image Super Resolution
  • 1. Intro.mp4 (9.6 MB)
  • 1. Intro.srt (1.5 KB)
  • 1.1 Image Super Resolution.zip.zip (9.4 MB)
  • 2. Quality Metrics and Preprocessing Images.mp4 (258.8 MB)
  • 2. Quality Metrics and Preprocessing Images.srt (44.3 KB)
  • 3. Image Super Resolution using Deep Learning.mp4 (357.6 MB)
  • 3. Image Super Resolution using Deep Learning.srt (55.1 KB)
12. Project 7 Text Classification
  • 1. Intro.mp4 (5.0 MB)
  • 1. Intro.srt (1.4 KB)
  • 1.1 Text Classification.zip.zip (55.4 KB)
  • 2. Feature Engineering.mp4 (375.4 MB)
  • 2. Feature Engineering.srt (56.5 KB)
  • 3. Deploying Sklearn Classifiers.mp4 (204.2 MB)
  • 3. Deploying Sklearn Classifiers.srt (32.3 KB)
13. Project 8 - KMeans
  • 1. Intro.mp4 (11.2 MB)
  • 1. Intro.srt (1.6 KB)
  • 1.1 KMeans.zip.zip (189.1 KB)
  • 2. Preprocessing Images for Clustering.mp4 (230.9 MB)
  • 2. Preprocessing Images for Clustering.srt (46.0 KB)
  • 3. Evaluation and Visualization.mp4 (209.5 MB)
  • 3. Evaluation and Visualization.srt (34.8 KB)
14. Project 9 PCA
  • 1. Intro.mp4 (3.7 MB)
  • 1. Intro.srt (1.3 KB)
  • 1.1 PCA.zip.zip (219.6 KB)
  • 2. The Elbow Method.mp4 (114.2 MB)
  • 2. The Elbow Method.srt (29.1 KB)
  • 3. PCA Compression and Visualization.mp4 (185.0 MB)
  • 3. PCA Compression and Visualization.srt (36.1 KB)
2. Supervised Learning - part 1
  • 1. Introduction to Supervised Learning.mp4 (25.5 MB)
  • 1. Introduction to Supervised Learning.srt (18.3 KB)
  • 10. Quiz- Answers - Section 2.html (0.1 KB)
  • 10.1 Unit 2 Solutions.pdf.pdf (75.3 KB)
  • 2. Linear Methods for Classification.mp4 (34.1 MB)
  • 2. Linear Methods for Classification.srt (22.0 KB)
  • 3. Linear Methods for Regression.mp4 (27.0 MB)
  • 3. Linear Methods for Regression.srt (14.7 KB)
  • 4. Support Vector Machines.mp4 (35.8 MB)
  • 4. Support Vector Machines.srt (20.5 KB)
  • 5. Basis Expansions.mp4 (21.3 MB)
  • 5. Basis Expansions.srt (14.1 KB)
  • 6. Model Selection Procedures.mp4 (26.9 MB)
  • 6. Model Selection Procedures.srt (17.1 KB)
  • 7. Bonus! Supervised Learning Project in Python Part 1.mp4 (31.0 MB)
  • 7. Bonus! Supervised Learning Project in Python Part 1.srt (18.9 KB)
  • 7.1 Supervised Learning.zip.zip (167.2 KB)
  • 8. Bonus! Supervised Learning Project in Python Part 2.mp4 (36.2 MB)
  • 8. Bonus! Supervised Learning Project in Python Part 2.srt (17.8 KB)
  • 9. Quiz- Questions- Section 2.html (0.1 KB)
  • 9.1 Unit 2 Quiz.pdf.pdf (53.0 KB)
3. Unsupervised Learning
  • 1. Introduction to Unsupervised Learning.mp4 (31.8 MB)
  • 1. Introduction to Unsupervised Learning.srt (15.8 KB)
  • 2. Association Rules.mp4 (28.5 MB)
  • 2. Association Rules.srt (18.7 KB)
  • 3. Cluster Analysis.mp4 (28.0 MB)
  • 3. Cluster Analysis.srt (17.9 KB)
  • 4. Reinforcement Learning.mp4 (21.0 MB)
  • 4. Reinforcement Learning.srt (22.4 KB)
  • 5. Bonus! KMeans Clustering Project.mp4 (22.0 MB)
  • 5. Bonus! KMeans Clustering Project.srt (19.8 KB)
  • 5.1 Unsupervised Learning.zip.zip (92.5 KB)
  • 6. Quiz- Questions- Section 3.html (0.1 KB)
  • 6.1 Unit 3 Quiz.pdf.pdf (29.8 KB)
  • 7. Quiz- Answers - Section 3.html (0.1 KB)
  • 7.1 Unit 3 Solutions.pdf.pdf (41.3 KB)
4. Neural Networks
  • 1. Introduction to Neural Networks.mp4 (22.7 MB)
  • 1. Introduction to Neural Networks.srt (17.6 KB)
  • 2. The Perceptron.mp4 (17.1 MB)
  • 2. The Perceptron.srt (13.4 KB)
  • 3. The Backpropagation Algorithm.mp4 (22.6 MB)
  • 3. The Backpropagation Algorithm.srt (16.1 KB)
  • 4. Training Procedures.mp4 (24.0 MB)
  • 4. Training Procedures.srt (18.7 KB)
  • 5. Convolutional Neural Networks.mp4 (32.0 MB)
  • 5. Convolutional Neural Networks.srt (21.8 KB)
5. Real World Machine Learning
  • 1. Introduction to Real World ML.mp4 (25.6 MB)
  • 1. Introduction to Real World ML.srt (16.4 KB)
  • 2. Choosing an Algorithm.mp4 (19.1 MB)
  • 2. Choosing an Algorithm.srt (13.3 KB)
  • 3. Design and Analysis of ML Experiments.mp4 (19.8 MB)
  • 3. Design and Analysis of ML Experiments.srt (14.5 KB)
  • 4. Common Software for ML.mp4 (31.3 MB)
  • 4. Common Software for ML.srt (15.1 KB)
  • 5. Quiz- Quest

Description

Udemy - Projects in Machine Learning : Beginner To Professional [TP]

A complete guide to master machine learning concepts and create real world ML solutions

For more Udemy Courses: https://tutorialsplanet.net



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Udemy - Projects in Machine Learning : Beginner To Professional [TP]

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4.2 GB
seeders:21
leechers:18
Udemy - Projects in Machine Learning : Beginner To Professional [TP]

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