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Название [FreeTutorials.Us] Udemy - Projects in Machine Learning Beginner To Professional
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[FreeCoursesOnline.Me].url 133б
[FreeTutorials.Us].url 119б
[FTU Forum].url 252б
1.1 Board Game Review Predictions.zip.zip 128.63Кб
1.1 Credit Card Fraud Detection.zip.zip 237.75Кб
1.1 Final Project.zip.zip 47.02Кб
1.1 Image Super Resolution.zip.zip 9.41Мб
1.1 Intro to Natural Language Processing.zip.zip 64.95Кб
1.1 KMeans.zip.zip 189.11Кб
1.1 Object Recognition.zip.zip 219.04Кб
1.1 PCA.zip.zip 219.64Кб
1.1 Text Classification.zip.zip 55.36Кб
1. Intro.mp4 7.21Мб
1. Intro.mp4 9.56Мб
1. Intro.mp4 5.00Мб
1. Intro.mp4 11.21Мб
1. Intro.mp4 3.69Мб
1. Intro.mp4 7.55Мб
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1. Intro.mp4 16.95Мб
1. Intro.srt 1.66Кб
1. Intro.srt 1.51Кб
1. Intro.srt 1.39Кб
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1. Intro.srt 1.30Кб
1. Intro.srt 2.02Кб
1. Intro.srt 2.80Кб
1. Intro.srt 1.66Кб
1. Introduction.mp4 1.71Мб
1. Introduction.srt 1.63Кб
1. Introduction to Neural Networks.mp4 22.71Мб
1. Introduction to Neural Networks.srt 17.55Кб
1. Introduction to Real World ML.mp4 25.58Мб
1. Introduction to Real World ML.srt 16.38Кб
1. Introduction to Supervised Learning.mp4 25.47Мб
1. Introduction to Supervised Learning.srt 18.30Кб
1. Introduction to Unsupervised Learning.mp4 31.78Мб
1. Introduction to Unsupervised Learning.srt 15.81Кб
1. Setting up OpenAI Gym.mp4 30.12Мб
1. Setting up OpenAI Gym.srt 17.17Кб
10.1 Unit 2 Solutions.pdf.pdf 75.28Кб
10. Quiz- Answers - Section 2.html 53б
2. Association Rules.mp4 28.50Мб
2. Association Rules.srt 18.71Кб
2. Board Game Review Prediction - Building the Dataset Part 1.mp4 17.73Мб
2. Board Game Review Prediction - Building the Dataset Part 1.srt 12.67Кб
2. Building and Training the Network Part 1.mp4 36.02Мб
2. Building and Training the Network Part 1.srt 20.35Кб
2. Choosing an Algorithm.mp4 19.14Мб
2. Choosing an Algorithm.srt 13.28Кб
2. Credit Card Fraud Detection - The Dataset.mp4 37.57Мб
2. Credit Card Fraud Detection - The Dataset.srt 26.52Кб
2. Feature Engineering.mp4 375.39Мб
2. Feature Engineering.srt 56.48Кб
2. Linear Methods for Classification.mp4 34.14Мб
2. Linear Methods for Classification.srt 21.99Кб
2. Loading and Preprocessing the CIFAR10 Dataset.mp4 180.54Мб
2. Loading and Preprocessing the CIFAR10 Dataset.srt 32.63Кб
2. Preprocessing Images for Clustering.mp4 230.86Мб
2. Preprocessing Images for Clustering.srt 45.96Кб
2. Quality Metrics and Preprocessing Images.mp4 258.79Мб
2. Quality Metrics and Preprocessing Images.srt 44.26Кб
2. The Elbow Method.mp4 114.20Мб
2. The Elbow Method.srt 29.11Кб
2. The Perceptron.mp4 17.12Мб
2. The Perceptron.srt 13.35Кб
2. Tokenizing, Stop Words, and Stemming.mp4 198.34Мб
2. Tokenizing, Stop Words, and Stemming.srt 30.14Кб
2. What is Machine Learning.mp4 29.19Мб
2. What is Machine Learning.srt 15.77Кб
3. Board Game Review Prediction - Building the Dataset Part 2.mp4 35.50Мб
3. Board Game Review Prediction - Building the Dataset Part 2.srt 20.37Кб
3. Building and Deploying the All-CNN Network Part 1.mp4 205.60Мб
3. Building and Deploying the All-CNN Network Part 1.srt 30.70Кб
3. Building and Training the Network Part 2.mp4 63.34Мб
3. Building and Training the Network Part 2.srt 26.95Кб
3. Cluster Analysis.mp4 27.95Мб
3. Cluster Analysis.srt 17.86Кб
3. Credit Card Fraud Detection - The Algorithms.mp4 48.91Мб
3. Credit Card Fraud Detection - The Algorithms.srt 24.93Кб
3. Deploying Sklearn Classifiers.mp4 204.23Мб
3. Deploying Sklearn Classifiers.srt 32.28Кб
3. Design and Analysis of ML Experiments.mp4 19.79Мб
3. Design and Analysis of ML Experiments.srt 14.47Кб
3. Evaluation and Visualization.mp4 209.48Мб
3. Evaluation and Visualization.srt 34.79Кб
3. Image Super Resolution using Deep Learning.mp4 357.57Мб
3. Image Super Resolution using Deep Learning.srt 55.11Кб
3. Linear Methods for Regression.mp4 27.01Мб
3. Linear Methods for Regression.srt 14.73Кб
3. PCA Compression and Visualization.mp4 185.00Мб
3. PCA Compression and Visualization.srt 36.13Кб
3. Tagging, Chunking, and Named Entity Recognition.mp4 323.06Мб
3. Tagging, Chunking, and Named Entity Recognition.srt 37.42Кб
3. The Backpropagation Algorithm.mp4 22.64Мб
3. The Backpropagation Algorithm.srt 16.14Кб
3. Types and Applications of ML.mp4 53.05Мб
3. Types and Applications of ML.srt 34.78Кб
4. AI vs ML.mp4 22.88Мб
4. AI vs ML.srt 12.52Кб
4. Board Game Review Prediction - Training the Models.mp4 35.82Мб
4. Board Game Review Prediction - Training the Models.srt 16.81Кб
4. Building and Deploying the All-CNN Network Part 2.mp4 170.79Мб
4. Building and Deploying the All-CNN Network Part 2.srt 25.32Кб
4. Common Software for ML.mp4 31.33Мб
4. Common Software for ML.srt 15.09Кб
4. Reinforcement Learning.mp4 20.96Мб
4. Reinforcement Learning.srt 22.35Кб
4. Support Vector Machines.mp4 35.79Мб
4. Support Vector Machines.srt 20.46Кб
4. Text Classification.mp4 216.93Мб
4. Text Classification.srt 29.66Кб
4. Training Procedures.mp4 24.04Мб
4. Training Procedures.srt 18.74Кб
5.1 Unit 5 Quiz.pdf.pdf 35.22Кб
5.1 Unsupervised Learning.zip.zip 92.48Кб
5. Basis Expansions.mp4 21.32Мб
5. Basis Expansions.srt 14.06Кб
5. Bonus! KMeans Clustering Project.mp4 21.95Мб
5. Bonus! KMeans Clustering Project.srt 19.77Кб
5. Convolutional Neural Networks.mp4 32.04Мб
5. Convolutional Neural Networks.srt 21.82Кб
5. Essential Math for ML and AI.mp4 35.79Мб
5. Essential Math for ML and AI.srt 23.34Кб
5. Quiz- Questions- Section 5.html 65б
6.1 Unit 1 Quiz.pdf.pdf 64.52Кб
6.1 Unit 3 Quiz.pdf.pdf 29.80Кб
6.1 Unit 5 Solutions.pdf.pdf 47.20Кб
6. Model Selection Procedures.mp4 26.93Мб
6. Model Selection Procedures.srt 17.05Кб
6. Quiz- Answers - Section 5.html 53б
6. Quiz- Questions- Section1.html 65б
6. Quiz- Questions- Section 3.html 65б
7.1 Supervised Learning.zip.zip 167.22Кб
7.1 Unit 1 Solutions.pdf.pdf 61.74Кб
7.1 Unit 3 Solutions.pdf.pdf 41.25Кб
7. Bonus! Supervised Learning Project in Python Part 1.mp4 31.01Мб
7. Bonus! Supervised Learning Project in Python Part 1.srt 18.94Кб
7. Quiz- Answers - Section 1.html 53б
7. Quiz- Answers - Section 3.html 53б
8. Bonus! Supervised Learning Project in Python Part 2.mp4 36.22Мб
8. Bonus! Supervised Learning Project in Python Part 2.srt 17.81Кб
9.1 Unit 2 Quiz.pdf.pdf 52.97Кб
9. Quiz- Questions- Section 2.html 65б
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