Learn · Practical Machine Learning with Tensorflow
Lecture 1 of 39Week 1
Overview of Tensorflow
Prof. Ashish Tendulkar and Prof. Balaraman Ravindran · IIT Madras & Google
Credits and licence
- From
- Practical Machine Learning with Tensorflow, IIT Madras & Google (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- 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
- Tweens profiles and older. How courses are placed
All the lectures
- Overview of Tensorflow
- Machine Learning Refresher
- Steps in Machine Learning Process
- Loss Functions in Machine Learning
- Gradient Descent
- Gradient Descent Variations
- Model Selection and Evaluation
- Machine Learning Visualization
- Deep Learning Refresher
- Introduction to Tensors
- 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
- Classify Images
- Regression
- Classify Structured Data
- Text Classification
- Underfitting and Overfitting
- Save and Restore Models
- CNNs-Part 1
- CNNs-Part 2
- Transfer learning with pretrained CNNs
- Transfer learning with TF hub
- Image classification and visualization
- Estimator API
- Logistic Regression
- Boosted Trees
- Introduction to word embeddings
- Recurrent Neural Networks (Part 1)
- Recurrent Neural Networks (Part 2)
- Time Series Forecasting with RNNs
- Text Generation with RNNs.
- TensorFlow Customization
- Customizing tf.keras - Part 1
- Customizing tf.keras - Part 2
- TensorFlow Distributed Training
- Live Session 14-09-2019