Tutorialsplanet NET Udemy Data Science Supervised Machine Learning in Python

Tutorialsplanet NET Udemy Data Science Supervised Machine Learning in Python

Name	[Tutorialsplanet.NET] Udemy - Data Science Supervised Machine Learning in Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.1 GB
Total Files	107
Hash	E364B80AEC5C61F1A6E6571B43FB31AC758F31A7

/1. Introduction and Review/
1. Introduction and Outline.mp4	8.0 MB
1. Introduction and Outline.srt	5.8 KB
2. Review of Important Concepts.mp4	6.3 MB
2. Review of Important Concepts.srt	4.5 KB
3. Where to get the Code and Data.mp4	4.1 MB
3. Where to get the Code and Data.srt	2.7 KB
4. How to Succeed in this Course.mp4	3.5 MB
4. How to Succeed in this Course.srt	4.1 KB
/10. Extra Help With Python Coding for Beginners/
1. How to Code by Yourself (part 1).mp4	25.7 MB
1. How to Code by Yourself (part 1).srt	23.3 KB
2. How to Code by Yourself (part 2).mp4	15.5 MB
2. How to Code by Yourself (part 2).srt	13.6 KB
3. Proof that using Jupyter Notebook is the same as not using it.mp4	82.1 MB
3. Proof that using Jupyter Notebook is the same as not using it.srt	14.5 KB
4. Python 2 vs Python 3.mp4	8.2 MB
4. Python 2 vs Python 3.srt	6.2 KB
/11. Effective Learning Strategies for Machine Learning/
1. How to Succeed in this Course (Long Version).mp4	13.6 MB
1. How to Succeed in this Course (Long Version).srt	15.0 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	40.9 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt	32.5 KB
3. What order should I take your courses in (part 1).mp4	30.8 MB
3. What order should I take your courses in (part 1).srt	16.4 KB
4. What order should I take your courses in (part 2).mp4	39.4 MB
4. What order should I take your courses in (part 2).srt	23.6 KB
/12. Appendix FAQ/
1. What is the Appendix.mp4	5.7 MB
1. What is the Appendix.srt	3.8 KB
2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4	39.7 MB
2. BONUS Where to get Udemy coupons and FREE deep learning material.srt	8.1 KB
/2. K-Nearest Neighbor/
1. K-Nearest Neighbor Intuition.mp4	18.4 MB
1. K-Nearest Neighbor Intuition.srt	5.0 KB
2. K-Nearest Neighbor Concepts.mp4	9.0 MB
2. K-Nearest Neighbor Concepts.srt	6.4 KB
3. KNN in Code with MNIST.mp4	18.8 MB
3. KNN in Code with MNIST.srt	7.5 KB
4. When KNN Can Fail.mp4	8.1 MB
4. When KNN Can Fail.srt	4.7 KB
5. KNN for the XOR Problem.mp4	4.5 MB
5. KNN for the XOR Problem.srt	2.2 KB
6. KNN for the Donut Problem.mp4	5.7 MB
6. KNN for the Donut Problem.srt	2.6 KB
7. Effect of K.mp4	37.6 MB
7. Effect of K.srt	7.2 KB
8. KNN Exercise.mp4	17.7 MB
8. KNN Exercise.srt	5.6 KB
9. Suggestion Box.mp4	16.9 MB
9. Suggestion Box.srt	4.8 KB
/3. Naive Bayes and Bayes Classifiers/
1. Bayes Classifier Intuition (Continuous).mp4	84.1 MB
1. Bayes Classifier Intuition (Continuous).srt	23.5 KB
2. Bayes Classifier Intuition (Discrete).mp4	52.5 MB
2. Bayes Classifier Intuition (Discrete).srt	13.2 KB
3. Naive Bayes.mp4	16.5 MB
3. Naive Bayes.srt	11.8 KB
4. Naive Bayes Handwritten Example.mp4	6.1 MB
4. Naive Bayes Handwritten Example.srt	3.7 KB
5. Naive Bayes in Code with MNIST.mp4	15.1 MB
5. Naive Bayes in Code with MNIST.srt	4.9 KB
6. Non-Naive Bayes.mp4	7.7 MB
6. Non-Naive Bayes.srt	5.0 KB
7. Bayes Classifier in Code with MNIST.mp4	4.7 MB
7. Bayes Classifier in Code with MNIST.srt	1.6 KB
8. Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).mp4	10.9 MB
8. Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).srt	7.6 KB
9. Generative vs Discriminative Models.mp4	5.4 MB
9. Generative vs Discriminative Models.srt	3.2 KB
/4. Decision Trees/
1. Decision Tree Intuition.mp4	21.4 MB
1. Decision Tree Intuition.srt	5.7 KB
2. Decision Tree Basics.mp4	8.7 MB
2. Decision Tree Basics.srt	6.3 KB
3. Information Entropy.mp4	7.3 MB
3. Information Entropy.srt	4.4 KB
4. Maximizing Information Gain.mp4	14.6 MB
4. Maximizing Information Gain.srt	9.9 KB
5. Choosing the Best Split.mp4	7.1 MB
5. Choosing the Best Split.srt	4.9 KB
6. Decision Tree in Code.mp4	31.8 MB
6. Decision Tree in Code.srt	11.4 KB
/5. Perceptrons/
1. Perceptron Concepts.mp4	12.8 MB
1. Perceptron Concepts.srt	8.9 KB
2. Perceptron in Code.mp4	14.4 MB
2. Perceptron in Code.srt	4.8 KB
3. Perceptron for MNIST and XOR.mp4	9.2 MB
3. Perceptron for MNIST and XOR.srt	2.4 KB
4. Perceptron Loss Function.mp4	6.6 MB
4. Perceptron Loss Function.srt	5.0 KB
/6. Practical Machine Learning/
1. Hyperparameters and Cross-Validation.mp4	7.8 MB
1. Hyperparameters and Cross-Validation.srt	5.2 KB
2. Feature Extraction and Feature Selection.mp4	7.4 MB
2. Feature Extraction and Feature Selection.srt	5.0 KB
3. Comparison to Deep Learning.mp4	9.1 MB
3. Comparison to Deep Learning.srt	6.2 KB
4. Multiclass Classification.mp4	5.9 MB
4. Multiclass Classification.srt	4.2 KB
5. Sci-Kit Learn.mp4	16.6 MB
5. Sci-Kit Learn.srt	11.4 KB
6. Regression with Sci-Kit Learn is Easy.mp4	11.3 MB
6. Regression with Sci-Kit Learn is Easy.srt	6.2 KB
/7. Building a Machine Learning Web Service/
1. Building a Machine Learning Web Service Concepts.mp4	7.6 MB
1. Building a Machine Learning Web Service Concepts.srt	5.5 KB
2. Building a Machine Learning Web Service Code.mp4	12.5 MB
2. Building a Machine Learning Web Service Code.srt	7.6 KB
/8. Conclusion/
1. What’s Next Support Vector Machines and Ensemble Methods (e.g. Random Forest).mp4	6.6 MB
1. What’s Next Support Vector Machines and Ensemble Methods (e.g. Random Forest).srt	3.6 KB
/9. Setting Up Your Environment/
1. Windows-Focused Environment Setup 2018.mp4	195.4 MB
1. Windows-Focused Environment Setup 2018.srt	20.6 KB
2. How to install Numpy, Scipy, Matplotlib, and Sci-Kit Learn.mp4	46.1 MB
2. How to install Numpy, Scipy, Matplotlib, and Sci-Kit Learn.srt	14.8 KB
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 107