Course10610621339 lectures
Practical Machine Learning with Tensorflow
Prof. Ashish Tendulkar and Prof. Balaraman Ravindran · IIT Madras & Google
Lectures
Week 1
- Overview of Tensorflow
- Machine Learning Refresher
- Steps in Machine Learning Process
- Loss Functions in Machine Learning
- Gradient Descent
Week 2
- Gradient Descent Variations
- Model Selection and Evaluation
- Machine Learning Visualization
- Deep Learning Refresher
- Introduction to Tensors
Week 3
- Mathematical Foundations of Deep Learning - Contd.
- Building Data Pipelines for Tensorflow-Part 1
- Building Data Pipelines for Tensorflow-Part 2
- Building Data Pipelines for Tensorflow-Part 3
- Text Processing with Tensorflow
Week 4
- Classify Images
- Regression
- Classify Structured Data
- Text Classification
- Underfitting and Overfitting
- Save and Restore Models
Week 5
- CNNs-Part 1
- CNNs-Part 2
- Transfer learning with pretrained CNNs
- Transfer learning with TF hub
- Image classification and visualization
Week 6
Week 7
- Introduction to word embeddings
- Recurrent Neural Networks (Part 1)
- Recurrent Neural Networks (Part 2)
- Time Series Forecasting with RNNs
- Text Generation with RNNs.
Week 8
- TensorFlow Customization
- Customizing tf.keras - Part 1
- Customizing tf.keras - Part 2
- TensorFlow Distributed Training
Live Session
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Madras & Google
- Department
- Computer Science and Engineering
- Taught by
- Prof. Ashish Tendulkar, Prof. Balaraman Ravindran
- Level
- Undergraduate
- Language
- English
- Subjects
- Computer science, Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed
More like this
TED
Talk
The future we're building -- and boring
Source's player
TED
Talk
The thrilling potential of SixthSense technology
Source's player
TED
Talk
Why don't perpetual motion machines ever work?
Source's player
Course
History 7b Spring 2006 UC Berkeley (History 7B US History: from Civil War to Present)
39 lectures · Audio
Course
Science Events Video
84 lectures · Video
Course
Nuclear Engineering 101 001 Fall 2009 UC Berkeley Nuclear Reactions and Radiation (Nuclear Engineering 101, 001|Fall 2009|UC Berkeley (Nuclear Reactions and Radiation))
29 lectures · Audio
Course
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
34 lectures · Video
Course
Computational Science and Engineering I
50 lectures · Video
Course
Engineering Dynamics
223 lectures · Video
Course
CS50’s Introduction to Computer Science
12 lectures · Video
Course
Frontiers of Biomedical Engineering
25 lectures · Audio
Course
CS50's Introduction to Programming with Python
10 lectures · Video
Course
Matrix Methods in Data Analysis, Signal Processing, and Machine Learning
34 lectures · Video
Course
Computational Science and Engineering I
50 lectures · Video
Course
Engineering Dynamics
223 lectures · Video
Course
CS50’s Introduction to Computer Science
12 lectures · Video
Course
Frontiers of Biomedical Engineering
25 lectures · Audio
Course
CS50's Introduction to Programming with Python
10 lectures · Video