课程信息
4.8
58 个评分
12 个审阅
专项课程

第 2 门课程(共 4 门),位于

100% online

100% online

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

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高级

高级

完成时间(小时)

完成时间大约为20 小时

建议:16 hours/week...
可选语言

英语(English)

字幕:英语(English)...
专项课程

第 2 门课程(共 4 门),位于

100% online

100% online

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
高级

高级

完成时间(小时)

完成时间大约为20 小时

建议:16 hours/week...
可选语言

英语(English)

字幕:英语(English)...

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 5 小时

Setting the stage

...
Reading
10 个视频(共 59 分钟), 2 个阅读材料, 3 个测验
Video10 个视频
Linear algebra5分钟
High Dimensional Vector Spaces2分钟
Supervised vs. Unsupervised Machine Learning4分钟
How ML Pipelines work3分钟
Introduction to SparkML20分钟
What is SystemML (1/2) ?3分钟
What is SystemML (2/2) ?6分钟
How to use Apache SystemML in IBM Watson Studio4分钟
Extract - Transform - Load3分钟
Reading2 个阅读材料
Object Store10分钟
Latest Video summary on environment setup10分钟
Quiz2 个练习
Machine Learning12分钟
ML Pipelines6分钟
2
完成时间(小时)
完成时间为 6 小时

Supervised Machine Learning

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

Unsupervised Machine Learning

...
Reading
13 个视频(共 67 分钟), 1 个阅读材料, 3 个测验
Video13 个视频
Introduction to Clustering: k-Means3分钟
Hierarchical Clustering3分钟
Density-based clustering (Guest Lecture Saeed Aghabozorgi)4分钟
Using K-Means in Apache SparkML2分钟
Curse of Dimensionality9分钟
Dimensionality Reduction4分钟
Principal Component Analysis6分钟
Principal Component Analysis (demo)6分钟
Covariance matrix and direction of greatest variance8分钟
Eigenvectors and eigenvalues8分钟
Projecting the data4分钟
PCA in SystemML2分钟
Reading1 个阅读材料
Reading on Clustering Evaluation and Assessment10分钟
Quiz2 个练习
Clustering4分钟
PCA16分钟
4
完成时间(小时)
完成时间为 5 小时

Digital Signal Processing in Machine Learning

...
Reading
13 个视频(共 108 分钟), 3 个测验
Video13 个视频
Fourier Transform in action6分钟
Signal generation and phase shift11分钟
The maths behind Fourier Transform11分钟
Discrete Fourier Transform16分钟
Fourier Transform in SystemML15分钟
Fast Fourier Transform7分钟
Nonstationary signals5分钟
Scaleograms7分钟
Continous Wavelet Transform3分钟
Scaling and translation3分钟
Wavelets and Machine Learning3分钟
Wavelets transform and SVM demo6分钟
Quiz2 个练习
Fourier Transform16分钟
Wavelet Transform16分钟
4.8
12 个审阅Chevron Right

热门审阅

创建者 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.

创建者 IMJun 26th 2018

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

讲师

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT
Avatar

Nikolay Manchev

Data Scientist
IBM EMEA Data Science

关于 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....

关于 Advanced Data Science with IBM 专项课程

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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