課程信息
56,805

第 3 門課程(共 4 門)

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

根據您的日程表重置截止日期。

高級

完成時間大約為19 小時

建議:4 weeks of study, 4-6 hours/week...

英語(English)

字幕:英語(English)

您將獲得的技能

Machine LearningDeep LearningLong Short-Term Memory (ISTM)Apache Spark

第 3 門課程(共 4 門)

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

根據您的日程表重置截止日期。

高級

完成時間大約為19 小時

建議:4 weeks of study, 4-6 hours/week...

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
完成時間為 5 小時

Introduction to deep learning

...
17 個視頻 (總計 65 分鐘), 5 個閱讀材料, 2 個測驗
17 個視頻
Introduction - Romeo Kienzler30
Introduction - Ilja Rasin1分鐘
Introduction - Niketan Pansare30
Introduction - Tom Hanlon1分鐘
Course Logistics1分鐘
Cloud Architectures for AI and DeepLearning4分鐘
Linear algebra6分鐘
Deep feed forward neural networks12分鐘
Convolutional Neural Networks4分鐘
Recurrent neural networks1分鐘
LSTMs3分鐘
Auto encoders and representation learning2分鐘
Methods for neural network training8分鐘
Gradient Descent Updater Strategies6分鐘
How to choose the correct activation function3分鐘
The bias-variance tradeoff in deep learning3分鐘
5 個閱讀材料
IBM Digital Badge10分鐘
Video summary on environment setup10分鐘
Where to get all the code and slides for download?10分鐘
Introduction to ApacheSpark10分鐘
Link to Github10分鐘
1 個練習
DeepLearning Fundamentals14分鐘
2
完成時間為 7 小時

deep learning frameworks

...
24 個視頻 (總計 168 分鐘), 1 個閱讀材料, 5 個測驗
24 個視頻
Neural Network Debugging with TensorBoard7分鐘
Automatic Differentiation2分鐘
Introduction video44
Keras overview5分鐘
Sequential models in keras6分鐘
Feed forward networks7分鐘
Recurrent neural networks9分鐘
Beyond sequential models: the functional API3分鐘
Saving and loading models2分鐘
What is SystemML (1/2) ?3分鐘
What is SystemML (2/2) ?6分鐘
Demo - How to use Apache SystemML on IBM DSX (1/3)4分鐘
Demo - How to use Apache SystemML on IBM DSX (2/3)3分鐘
Demo - How to use Apache SystemML on IBM DSX (3/3)8分鐘
Introduction to DeepLearning4J12分鐘
Demo: Running Java in Data Science Experience8分鐘
DL4J Neural Network Code Example, Mnist Classifier14分鐘
PyTorch Installation2分鐘
PyTorch Packages2分鐘
Tensor Creation and Visualization of Higher Dimensional Tensors6分鐘
Math Computation and Reshape7分鐘
Computation Graph, CUDA17分鐘
Linear Model17分鐘
1 個閱讀材料
Link to files in Github10分鐘
4 個練習
TensorFlow12分鐘
Apache SystemML12分鐘
DL4J Fundamentals12分鐘
PyTorch Introduction12分鐘
3
完成時間為 6 小時

DeepLearning Applications

...
18 個視頻 (總計 115 分鐘), 2 個閱讀材料, 5 個測驗
18 個視頻
How to implement an anomaly detector (1/2)11分鐘
How to implement an anomaly detector (2/2)2分鐘
How to deploy a real-time anomaly detector2分鐘
Introduction to Time Series Forecasting4分鐘
Stateful vs. Stateless LSTMs6分鐘
Batch Size5分鐘
Number of Time Steps, Epochs, Training and Validation8分鐘
Trainin Set Size4分鐘
Input and Output Data Construction7分鐘
Designing the LSTM network in Keras10分鐘
Anatomy of a LSTM Node12分鐘
Number of Parameters7分鐘
Training and loading a saved model4分鐘
Classifying the MNIST dataset with Convolutional Neural Networks5分鐘
Image classification with Imagenet and Resnet503分鐘
Autoencoder - understanding Word2Vec8分鐘
Text Classification with Word Embeddings4分鐘
2 個閱讀材料
Generative Adversarial Networks (GANs) (optional)10分鐘
Generative Adversarial Networks (GANs) (optional)10分鐘
4 個練習
Anomaly Detection12分鐘
Sequence Classification with Keras LSTM Network12分鐘
Image Classification6分鐘
NLP6分鐘
4
完成時間為 4 小時

scaling and deployment

...
5 個視頻 (總計 40 分鐘), 3 個閱讀材料, 2 個測驗
5 個視頻
Creating and Scaling a Keras Model in ApacheSpark using DL4J14分鐘
Creating and Scaling a Keras Model in ApacheSpark using DL4J (Demo)16分鐘
Computer Vision with IBM Watson Visual Recognition2分鐘
Text Classification with IBM Watson Natural Language Classifier1分鐘
3 個閱讀材料
Parallel Neural Network Training10分鐘
Scale a Keras Model with IBM Watson Machine Learning10分鐘
Link to Github10分鐘
1 個練習
Run a Notebook using Keras and DL4J6分鐘
4.4
55 個審閱Chevron Right

18%

完成這些課程後已開始新的職業生涯

29%

通過此課程獲得實實在在的工作福利

33%

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熱門審閱

創建者 RCApr 26th 2018

It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea

創建者 QLApr 9th 2019

This is an excellent course in teaching me not only the deep learning principles but also practical usecases and various frameworks.

講師

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Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT
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Niketan Pansare

Senior Software Engineer
IBM Research
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Tom Hanlon

Training Director
Skymind
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Max Pumperla

Deep Learning Engineer
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Ilja Rasin

Data Scientist
IBM Watson Health

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

常見問題

  • 注册以便获得证书后,您将有权访问所有视频、测验和编程作业(如果适用)。只有在您的班次开课之后,才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程,可能无法访问某些作业。

  • 您注册课程后,将有权访问专项课程中的所有课程,并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中,您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容,可以免费旁听课程。

  • The IBM Watson IoT Certified Data Scientist degree is a Coursera specialization IBM is currently creating. This course is one part of 3-4 courses coming up the next couple of months

    Currently only this and another course exist. The other one is the following:

    https://www.coursera.org/learn/exploring-visualizing-iot-data

    The course above will be modified and renamed to "Fundamentals of Applied DataScience" - but if you pass it today, it counts towards the certificate as well

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