About this Course
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Intermediate Level

English

Subtitles: English

Skills you will gain

ForecastingMachine LearningTensorflowTime Seriesprediction

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
1 hour to complete

Sequences and Prediction

Hi Learners and welcome to this course on sequences and prediction! In this course we'll take a look at some of the unique considerations involved when handling sequential time series data -- where values change over time, like the temperature on a particular day, or the number of visitors to your web site. We'll discuss various methodologies for predicting future values in these time series, building on what you've learned in previous courses!

...
10 videos (Total 33 min), 2 readings
10 videos
SP W1 L1 Part 1- Time series examples4m
SP W1 L1 Part 2 - Machine Learning applied to Time Series1m
SP W1 L1 Part 3 - Common patterns in time series5m
SP W1 L2 Intro to time series notebook4m
SP W1 L3 Part 1 - Train validation test sets3m
SP W1 L3 Part 2 - Metrics to evaluate performance2m
SP W1 L3 Part 3 Moving average and differencing2m
SP W1 L3 Part 4 Trailing versus centered windows1m
SP W1 L4 - Forecasting notebook4m
2 readings
Notebook link10m
Week 1 Outro10m
Week
2
1 hour to complete

Deep Neural Network for time series

Having explored time series and some of the common attributes of time series such as trend and seasonality, and then having used statistical methods for projection, let's now begin to teach neural networks to recognize and predict on time series!

...
10 videos (Total 27 min), 2 readings
10 videos
SP W2 L1 - preparing features and labels from time series4m
SP W2 L2 - Preparing features and labels notebook3m
SP W2 L3 Part 1 - Windowed dataset2m
SP W2 L3 Part 2 - Single layer neural network2m
SP W2 L3 Part 3 - Clarifications37s
SP W2 L3 Part 4 - Prediction2m
SP W2 L4 -Single layer Neural Network notebook2m
SP W2 L5 - Deep Neural Network4m
SP W2 L6 -Deep Neural Network notebook3m
2 readings
Sequence bias10m
Week 2 Outro10m
Week
3
1 hour to complete

Recurrent Neural Networks for time series

Recurrent Neural networks and Long Short Term Memory networks are really useful to classify and predict on sequential data. This week we'll explore using them with time series...

...
10 videos (Total 21 min), 3 readings
10 videos
SP W3 L1 Part 1 - RNN Conceptual Overview2m
SP W3 L1 Part 2 - Shape of the inputs to the RNN2m
SP W3 L1 Part 3 - Outputting a sequence1m
SP W3 L1 Part 4 - Lambda layers1m
SP W3 L2 - Adjusting the learning rate dynamically2m
SP W3 L3 - RNN notebook1m
SP W3 L4 Part 1- LSTM1m
SP W3 L4 Part 2 - Coding LSTMs2m
SP W3 L5 - LSTM notebook1m
3 readings
More info on Huber loss10m
Link to the LSTM lesson10m
Week 3 Outro10m
Week
4
1 hour to complete

Real-world time series data

On top of DNNs and RNNs, let's also add convolutions, and then put it all together using a real-world data series -- one which measures sunspot activity over hundreds of years, and see if we can predict using it.

...
11 videos (Total 24 min), 3 readings
11 videos
SP W4 L1 Part 1 - Convolutions part 158s
SP W4 L1 Part 2 - Bi-directional LSTMs3m
SP W4 L2 LSTMs notebook1m
SP W4 L3 Part 1 - Sunspots, real data3m
SP W4 L3 Part 2 - train and tune the model3m
SP W4 L3 Part 3 - Prediction1m
SP W4 L4 - Sunspots notebook1m
SP W4 L5 - Combining our tools to analyze sunspot data3m
Course Outro SP W4 L638s
Specialization Outro - A conversation with Andrew Ng2m
3 readings
Convolutional Neural Networks course10m
More on batch sizing10m
Course 4 Outro10m

Instructor

Avatar

Laurence Moroney

AI Advocate
Google Brain

About deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

About the TensorFlow in Practice Specialization

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Courses 1-3 are available now, with Course 4 launching in July....
TensorFlow in Practice

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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