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강의 계획 - 이 강좌에서 배울 내용

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1

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Setting the stage

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10개 동영상 (총 59분), 2 개의 읽기 자료, 3 개의 테스트
10개의 동영상
Linear algebra5m
High Dimensional Vector Spaces2m
Supervised vs. Unsupervised Machine Learning4m
How ML Pipelines work3m
Introduction to SparkML20m
What is SystemML (1/2) ?3m
What is SystemML (2/2) ?6m
How to use Apache SystemML in IBM Watson Studio4m
Extract - Transform - Load3m
2개의 읽기 자료
Object Store10m
IMPORTANT: How to submit your programming assignments10m
2개 연습문제
Machine Learning12m
ML Pipelines6m
2

2

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Supervised Machine Learning

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26개 동영상 (총 131분), 1 개의 읽기 자료, 10 개의 테스트
26개의 동영상
LinearRegression with Apache SparkML6m
Linear Regression using Apache SystemML3m
Batch Gradient Descent using Apache SystemML8m
The importance of validation data to prevent overfitting3m
Important evaluation measures2m
Logistic Regression1m
LogisticRegression with Apache SparkML4m
Probabilities refresher6m
Rules of probability and Bayes' theorem10m
The Gaussian distribution4m
Bayesian inference4m
Bayesian inference - example9m
Maximum a posteriori estimation5m
Bayesian inference in Python8m
Why is Naive Bayes "naive"7m
Support Vector Machines3m
Support Vector Machines using Apache SparkML8m
Crossvalidation1m
Hyper-parameter tuning using GridSearch3m
Decision Trees2m
Bootstrap Aggregation (Bagging) and RandomForest1m
Boosting and Gradient Boosted Trees6m
Gradient Boosted Trees with Apache SparkML2m
Hyperparameter-Tuning using GridSeach and CrossValidation in Apache SparkML on Gradient Boosted Trees3m
Regularization3m
1개의 읽기 자료
Classification evaluation measures10m
9개 연습문제
Linear Regression6m
Splitting and Overfitting2m
Evaluation Measures2m
Logistic Regression2m
Naive Bayes16m
Support Vector Machines2m
Testing, X-Validation, GridSearch4m
Enselble Learning4m
Regularization4m
3

3

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Unsupervised Machine Learning

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13개 동영상 (총 67분), 1 개의 읽기 자료, 3 개의 테스트
13개의 동영상
Introduction to Clustering: k-Means3m
Hierarchical Clustering3m
Density-based clustering (Guest Lecture Saeed Aghabozorgi)4m
Using K-Means in Apache SparkML2m
Curse of Dimensionality9m
Dimensionality Reduction4m
Principal Component Analysis6m
Principal Component Analysis (demo)6m
Covariance matrix and direction of greatest variance8m
Eigenvectors and eigenvalues8m
Projecting the data4m
PCA in SystemML2m
1개의 읽기 자료
Reading on Clustering Evaluation and Assessment10m
2개 연습문제
Clustering4m
PCA16m
4

4

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Digital Signal Processing in Machine Learning

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13개 동영상 (총 108분)
13개의 동영상
Fourier Transform in action6m
Signal generation and phase shift11m
The maths behind Fourier Transform11m
Discrete Fourier Transform16m
Fourier Transform in SystemML15m
Fast Fourier Transform7m
Nonstationary signals5m
Scaleograms7m
Continous Wavelet Transform3m
Scaling and translation3m
Wavelets and Machine Learning3m
Wavelets transform and SVM demo6m
2개 연습문제
Fourier Transform16m
Wavelet Transform16m

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