課程信息
4.8
60 個評分
12 個審閱
專項課程

第 2 門課程(共 4 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
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可靈活調整截止日期

根據您的日程表重置截止日期。
高級

高級

完成時間(小時)

完成時間大約為19 小時

建議:15 hours/week...
可選語言

英語(English)

字幕:英語(English)...
專項課程

第 2 門課程(共 4 門),位於

100% 在線

100% 在線

立即開始,按照自己的計劃學習。
可靈活調整截止日期

可靈活調整截止日期

根據您的日程表重置截止日期。
高級

高級

完成時間(小時)

完成時間大約為19 小時

建議:15 hours/week...
可選語言

英語(English)

字幕:英語(English)...

教學大綱 - 您將從這門課程中學到什麼

1
完成時間(小時)
完成時間為 5 小時

Setting the stage

...
Reading
10 個視頻(共 59 分鐘), 2 個閱讀材料, 3 個測驗
Video10 個視頻
Linear algebra5分鐘
High Dimensional Vector Spaces2分鐘
Supervised vs. Unsupervised Machine Learning4分鐘
How ML Pipelines work3分鐘
Introduction to SparkML20分鐘
What is SystemML (1/2) ?3分鐘
What is SystemML (2/2) ?6分鐘
How to use Apache SystemML in IBM Watson Studio4分鐘
Extract - Transform - Load3分鐘
Reading2 個閱讀材料
Object Store10分鐘
Latest Video summary on environment setup10分鐘
Quiz2 個練習
Machine Learning12分鐘
ML Pipelines6分鐘
2
完成時間(小時)
完成時間為 6 小時

Supervised Machine Learning

...
Reading
26 個視頻(共 131 分鐘), 1 個閱讀材料, 10 個測驗
Video26 個視頻
LinearRegression with Apache SparkML6分鐘
Linear Regression using Apache SystemML3分鐘
Batch Gradient Descent using Apache SystemML8分鐘
The importance of validation data to prevent overfitting3分鐘
Important evaluation measures2分鐘
Logistic Regression1分鐘
LogisticRegression with Apache SparkML4分鐘
Probabilities refresher6分鐘
Rules of probability and Bayes' theorem10分鐘
The Gaussian distribution4分鐘
Bayesian inference4分鐘
Bayesian inference - example9分鐘
Maximum a posteriori estimation5分鐘
Bayesian inference in Python8分鐘
Why is Naive Bayes "naive"7分鐘
Support Vector Machines3分鐘
Support Vector Machines using Apache SparkML8分鐘
Crossvalidation1分鐘
Hyper-parameter tuning using GridSearch3分鐘
Decision Trees2分鐘
Bootstrap Aggregation (Bagging) and RandomForest1分鐘
Boosting and Gradient Boosted Trees6分鐘
Gradient Boosted Trees with Apache SparkML2分鐘
Hyperparameter-Tuning using GridSeach and CrossValidation in Apache SparkML on Gradient Boosted Trees3分鐘
Regularization3分鐘
Reading1 個閱讀材料
Classification evaluation measures10分鐘
Quiz9 個練習
Linear Regression6分鐘
Splitting and Overfitting2分鐘
Evaluation Measures2分鐘
Logistic Regression2分鐘
Naive Bayes16分鐘
Support Vector Machines2分鐘
Testing, X-Validation, GridSearch4分鐘
Enselble Learning4分鐘
Regularization4分鐘
3
完成時間(小時)
完成時間為 5 小時

Unsupervised Machine Learning

...
Reading
13 個視頻(共 67 分鐘), 1 個閱讀材料, 3 個測驗
Video13 個視頻
Introduction to Clustering: k-Means3分鐘
Hierarchical Clustering3分鐘
Density-based clustering (Guest Lecture Saeed Aghabozorgi)4分鐘
Using K-Means in Apache SparkML2分鐘
Curse of Dimensionality9分鐘
Dimensionality Reduction4分鐘
Principal Component Analysis6分鐘
Principal Component Analysis (demo)6分鐘
Covariance matrix and direction of greatest variance8分鐘
Eigenvectors and eigenvalues8分鐘
Projecting the data4分鐘
PCA in SystemML2分鐘
Reading1 個閱讀材料
Reading on Clustering Evaluation and Assessment10分鐘
Quiz2 個練習
Clustering4分鐘
PCA16分鐘
4
完成時間(小時)
完成時間為 5 小時

Digital Signal Processing in Machine Learning

...
Reading
13 個視頻(共 108 分鐘), 3 個測驗
Video13 個視頻
Fourier Transform in action6分鐘
Signal generation and phase shift11分鐘
The maths behind Fourier Transform11分鐘
Discrete Fourier Transform16分鐘
Fourier Transform in SystemML15分鐘
Fast Fourier Transform7分鐘
Nonstationary signals5分鐘
Scaleograms7分鐘
Continous Wavelet Transform3分鐘
Scaling and translation3分鐘
Wavelets and Machine Learning3分鐘
Wavelets transform and SVM demo6分鐘
Quiz2 個練習
Fourier Transform16分鐘
Wavelet Transform16分鐘
4.8
12 個審閱Chevron Right

熱門審閱

創建者 ASep 8th 2018

A career changer course, thanks the hand-ons which is second to none, i have gained experience which on other online course can produce, thanks to IBM for this course which timely and excellent.

創建者 IMJun 26th 2018

Very well structured, easy to follow/understand. This is a hot topic at the moment and helped me in my job.

講師

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT
Avatar

Nikolay Manchev

Data Scientist
IBM EMEA Data Science

關於 IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

關於 Advanced Data Science with IBM 專項課程

As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....
Advanced Data Science with IBM

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