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Lecture 1: Overview of Tensorflow

Lecture 2: Machine Learning Refresher

Lecture 3: Steps in Machine Learning Process

Lecture 4: Loss Functions in Machine Learning

Lecture 5: Gradient Descent

Lecture 6: Gradient Descent Variations

Lecture 7: Model Selection and Evaluation

Lecture 8: Machine Learning Visualization

Lecture 9: Deep Learning Refresher

Lecture 10: Introduction to Tensors

Description:

COURSE OUTLINE: This will be an applied Machine Learning Course jointly offered by Google and IIT Madras. We will cover the basics of Tensorflow and Machine Learning in the initial sessions and advanced topics in the latter part. After this course, the students will be able to build ML models using Tensorflow.

Practical Machine Learning with Tensorflow

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#Computer Science #Machine Learning #Deep Learning #TensorFlow #Gradient Descent #Tensors #Loss Functions

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