UD460 | CC40FDAFA4F7DB13CA79B8EE9B16BC2FA5CCD068

UD460

Name	UD460	DOWNLOAD Copy Link
Total Size	1.1 GB
Total Files	53
Hash	CC40FDAFA4F7DB13CA79B8EE9B16BC2FA5CCD068

/01 Introduction and Review/
001 Introduction and Outline.mp4	8.0 MB
002 Review of Important Concepts.mp4	6.3 MB
003 Where to get the Code and Data.mp4	4.0 MB
004 How to Succeed in this Course.mp4	3.5 MB
/02 K-Nearest Neighbor/
005 K-Nearest Neighbor Intuition.mp4	18.4 MB
006 K-Nearest Neighbor Concepts.mp4	9.0 MB
007 KNN in Code with MNIST.mp4	18.8 MB
008 When KNN Can Fail.mp4	8.1 MB
009 KNN for the XOR Problem.mp4	4.5 MB
010 KNN for the Donut Problem.mp4	5.7 MB
011 Effect of K.mp4	37.5 MB
012 KNN Exercise.mp4	17.7 MB
013 Suggestion Box.mp4	16.9 MB
/03 Naive Bayes and Bayes Classifiers/
014 Bayes Classifier Intuition (Continuous).mp4	84.1 MB
015 Bayes Classifier Intuition (Discrete).mp4	52.5 MB
016 Naive Bayes.mp4	16.5 MB
017 Naive Bayes Handwritten Example.mp4	6.1 MB
018 Naive Bayes in Code with MNIST.mp4	15.1 MB
019 Non-Naive Bayes.mp4	7.7 MB
020 Bayes Classifier in Code with MNIST.mp4	4.7 MB
021 Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA).mp4	10.9 MB
022 Generative vs Discriminative Models.mp4	5.4 MB
/04 Decision Trees/
023 Decision Tree Intuition.mp4	21.4 MB
024 Decision Tree Basics.mp4	8.7 MB
025 Information Entropy.mp4	7.3 MB
026 Maximizing Information Gain.mp4	14.6 MB
027 Choosing the Best Split.mp4	7.0 MB
028 Decision Tree in Code.mp4	31.8 MB
/05 Perceptrons/
029 Perceptron Concepts.mp4	12.8 MB
030 Perceptron in Code.mp4	14.4 MB
031 Perceptron for MNIST and XOR.mp4	9.2 MB
032 Perceptron Loss Function.mp4	6.6 MB
/06 Practical Machine Learning/
033 Hyperparameters and Cross-Validation.mp4	7.8 MB
034 Feature Extraction and Feature Selection.mp4	7.4 MB
035 Comparison to Deep Learning.mp4	9.1 MB
036 Multiclass Classification.mp4	5.9 MB
037 Sci-Kit Learn.mp4	16.6 MB
038 Regression with Sci-Kit Learn is Easy.mp4	11.3 MB
/07 Building a Machine Learning Web Service/
039 Building a Machine Learning Web Service Concepts.mp4	7.6 MB
040 Building a Machine Learning Web Service Code.mp4	12.4 MB
/08 Conclusion/
041 Whats Next Support Vector Machines and Ensemble Methods (e.g. Random Forest).mp4	6.6 MB
/09 Appendix FAQ/
042 What is the Appendix.mp4	5.7 MB
043 BONUS Where to get Udemy coupons and FREE deep learning material.mp4	39.7 MB
044 Windows-Focused Environment Setup E8.mp4	195.4 MB
045 How to install Numpy Scipy Matplotlib and Sci-Kit Learn.mp4	46.0 MB
046 How to Code by Yourself (part 1).mp4	25.7 MB
047 How to Code by Yourself (part 2).mp4	15.5 MB
048 How to Succeed in this Course (Long Version).mp4	13.6 MB
049 Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	40.8 MB
050 Proof that using Jupyter Notebook is the same as not using it.mp4	82.1 MB
051 Python 2 vs Python 3.mp4	8.2 MB
052 What order should I take your courses in (part 1).mp4	30.7 MB
053 What order should I take your courses in (part 2).mp4	39.4 MB
Total files 53