Machine Learning for Engineering & Science Applications | IIT Madras - #70 LSTM | Machine Learning for Engineering & Science Applications

Unlock the Future: Master AI & Machine Learning with NPTEL-IITM’s Comprehensive Course! Dive into Neural Networks, Deep Learning, Probabilities, and Optimization Techniques tailored for Engineering & Science Applications. Your AI journey starts here!

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What you'll learn

Understand the historical development and foundational concepts of artificial intelligence.
Gain proficiency in applying machine learning techniques to engineering and science problems.
Develop skills in using linear algebra and calculus for machine learning modeling.
Learn to implement and optimize machine learning algorithms using Python packages.

This course includes

32 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

LSTM 10 Lec 28 04 03 19 Part 01

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! This lecture discusses the architecture of LSTMs in more detail. LSTMs use a memory cell to store information from previous time steps. They also use three gates: the forget gate, the input gate, and the output gate. The forget gate controls how much information from previous time steps is retained. The input gate controls how much new information is added to the memory cell. The output gate controls how much information from the memory cell is output to the next layer. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #RNN #LSTM #GRU #MemoryCell #ForgetGate #InputGate #OutputGate

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