Hardware for Deep Learning 2020

חומרה ללמידה עמוקה ובינה מלאכותית

Course lectures

1. Introduction to Deep Learning

HW for DL: Part 1a – From AI to DL

HW for DL: Part 1b – Introduction to Deep Learning – Training Neural Networks

DMC – Lecture 1: Introduction

Practice: RC Networks, Thevenin-Norton

Practice: Review of Digital Systems

1. Introduction to Deep Learning - slides

1. Introduction to Deep Learning - slides

2. Convolutional Neural Networks

HW for DL: Part 2a – Convolutional Neural Networks

HW for DL: Part 2b – Convolutional Neural Networks – Famous CNNs

English:
Section 2a: Verilog
Section 2b: Verilog Syntax
Section 2c: Simple Verilog Examples
Section 2d: Verilog FSM Implementation
Section 2e: Coding Style for RTL – part 1
Supplementary Material:
How to write Synthesizeable RTL
Kahoot! for discussing Lecture 2
עברית (Slides): Section 2a, 2b, 2c, 2d, 2e

עברית:
Section 1a
Section 1b
Section 1c
Section 1d

1. Introduction to Deep Learning - slides

1. Introduction to Deep Learning - slides

3. Computing Convolutions

HW for DL: Part 3 – Computing Convolutions

English:
Section 1a: Introduction
Section 1b: Building a Chip
Section 1c: Design Automation
Section 1d: The Chip Design Flow
Kahoot! for discussing Lecture 1

עברית:
Section 1a
Section 1b
Section 1c
Section 1d

1. Introduction to Deep Learning - slides

1. Introduction to Deep Learning - slides

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The Alexander Kofkin Faculty of Engineering

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Ramat Gan 5290002
Israel

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