Dive into Deep Learning: Coding Session #1 – Setup & MLP (APAC)
📌 Session #1 – Presentation of D2L, setup, and the MLP-model
📌 Introduction, Coding & Discussion
About:
The goal of these bi-weekly sessions is to provide code-focused sessions by reimplementing selected models from the book "Dive into Deep Learning". These sessions are meant for people who are interested in implementing models from scratch and/or never have implemented a model before. We hope to help participants either get started in their Machine Learning journey or deepen their knowledge if they already have previous experience.
We will try to achieve this by:
Helping participants to create their models end-to-end by reimplementing models from scratch, and discussing what modules/elements need to be included (e.g. data preprocessing, dataset generation, data transformation, etc…) to train an ML model.
Discussing and resolving coding questions participants might have during the sessions.
📌 Session Leads: Mrityunjay Bhardwaj, and Pierre Wüthrich
Mrityunjay Bhardwaj is the Head of AI at Jupiter AI Labs which focuses on providing research-oriented enterprise-grade ML Solutions. Apart from that, he is also trying his hand in ML research. / mrityunjay_99
Pierre Wüthrich is an AI Research Engineer at Elix Inc. focusing on drug discovery and material informatics. Before joining Elix, he gained experience in the field of applied reinforcement learning at another startup company specialized in machine automation through machine learning. / pierre-wuethrich
/ pierre_wuethri
● FULL CURRICULUM
📌 Session 1:
Coding env setup example and book presentation
Quick review of ML domains (supervised/unsupervised/RL)
General Architecture/Components of ML code
Implementation of simple MLP-model
📌 Session 2:
CNN model (LeNet/ResNet) implementation
📌 Session 3:
RNN model (LSTM) implementation
📌 Session 4:
Attention mechanism (Transformer) implementation
📌 Session 5:
Attention mechanism (Transformer) implementation
📌 Session 6:
Generative adversarial networks (DCGAN) implementation
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