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Online Meetup: Deep Learning Master Class Series

Online Meetup: Deep Learning Master Class Series

This series takes engineers from zero to expert in machine learning in 5 sessions. The world needs more people who understand machine learning, and our goal is to get you started on that path as efficiently as possible. While there are plenty of online resources, we know it's tough to learn a technical topic without a teacher. This workshop will arm you with the tools to get started using machine learning in your day job, and the resources to find additional help if you want to go deeper.

Jan 30 - Introduction

Deep Learning Architectures

  • Perception
  • MLPs
  • CNNs

Feb 06 - Computer Vision

We will discuss some of the more popular application of computer vision including

  • Object detection
  • Image segmentation
  • Bounding Boxes
  • Building convolutional neural networks
  • Image Recognition

Feb 13 - Model Performance, Quantization, & Hyperparameter Search

Deep Learning Architectures

  • LSTM/GRU Classifiers
  • CNN/LSTM hybrid
  • Sequence to Sequence models

Mar 20 - Intro to RNNs, LSTMs, and GRUs

Applications

  • Model Time Series aviation data with RNNs
  • Classify Text with LSTM/GRU
  • Generate Text with LSTM

Mar 24 - Recap

We will recap the previous four webinars and also announce next series!

Speaker

Lavanya Shukla is a machine learning engineer @ Weights and Biases. She began working on AI 10 years ago when she founded ACM SIGAI at Purdue University as a sophomore. In a past life, she taught herself to code at age 10, and built her first startup at 14. She's driven by a deep desire to understand the universe around us better by using machine learning. You can find her on twitter @lavanya.ai.

Workshop Materials

  1. Lavanaya's Neural Network Github
  2. RNN
  3. Intro to Keras
  4. Emotion Classifier
  5. Intro to CNN

Other Links

  1. IBM Cloud Sign Up for Part 1 - https://ibm.biz/BdqjCP
  2. W&B Forum
  3. Tensorflow word2vec visualizer
  4. IBM Model Asset Exchange
  5. NeRF - Representing Scenes as Neural Radiance Fields for View Synthesis
  6. Dot Product

Code Patterns

  1. Build an object detection model to identify license plates from images of cars
  2. Build a machine learning recommendation engine to encourage additional purchases based on past buying behavior
  3. Demand forecasting using deep learning
  4. Create a predictive system for image classification using Deep Learning as a Service
  5. Create a progressive web application for offline image classification

FAQs

  1. The video is paused for me, what do I do?

    You have to hit the play button in some browsers as the video does not auto play.

  2. Is this webinar being recorded?

    Yes, the webinar is being recorded, you can view the replay on the same link once the event ends.

Contact Us

If you have any questions about this webinar, please contact Upkar Lidder on LinkedIn.

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