DL course co-developed by YSDA, HSE and Skoltech

Related tags

Deep Learning course lasagne theano deep-learning course-materials
Overview

Deep learning course

This repo supplements Deep Learning course taught at YSDA and HSE @fall'21. For previous iteration visit the spring21 branch.

Lecture and practice materials for each week are in ./week* folders. You can complete all asignments locally or in google colab (see readme files in week*)

General info

  • Telegram chat room (russian).
  • Deadlines & grading rules can be found at this page.
  • Any technical issues, ideas, bugs in course materials, contribution ideas - add an issue

Syllabus

  • week01 Intro to deep learning

    • Lecture: Deep learning -- introduction, backpropagation algorithm, adaptive optimization methods
    • Seminar: Neural networks in numpy
    • Homework 1 is out!
    • Please begin worrying about installing pytorch. You will need it next week!

  • week02 Catch-all lecture about deep learning tricks

    • Lecture: Deep learning as a language, dropout, batch/layer normalization, other tricks, deep learning frameworks
    • Seminar: PyTorch basics

  • week03 Convolutional neural networks

    • Lecture: Computer vision tasks, Convolution and Pooling layers, ConvNet architectures, Data Augmentation
    • Seminar: Training your first ConvNet

Contributors & course staff

Course materials and teaching performed by

Comments
  • hw 0 - mark

    hw 0 - mark

    Hi!

    I sent my homework from [email protected] at 21.57 on Wensday, 28/09/2016. I sent another email (21/11/2016) when I didn't found myself in the grade sheet, but there was no answer. So I've posted an issue here.

    opened by MaximUshakov 3
  • Were the seminars recorded?

    Were the seminars recorded?

    Would like to know whether the seminars (in Russian) were recorded for the 2019 course or will there be recordings of the seminars for the 2020 course?

    opened by roboserg 2
  • Prettify week2 homework

    Prettify week2 homework

    Dear @justheuristic, if you want to check diff with your own eyes, take only the second commit, the first one is technical metadata changes and other jupyter stuff Yes, here we have only the fixes from Practical_RL repo

    opened by yhn112 1
  • resolve few typos

    resolve few typos

    Pytorch throws an exception when processing a backward pass from a variable that was obtained from the gaussian_sampler function, because exp_ and add_ are inplace functions. (pytorch version 1.4.0)

    Two typos in math, first -- we need to compute KL divergence between posterior and prior distributions, second -- just upper case typo.

    opened by a-domrachev 1
  • Fixing the issue regards Google Colab Visualization

    Fixing the issue regards Google Colab Visualization

    Fixing the issue regards Google Colab SHAP visualization. We can't visualize the TreeExplainer on google Colab without reinitializing the javascript again.

    opened by AI-Ahmed 1
  • `KeyedVector` removed in Gensim 4.0.0.

    `KeyedVector` removed in Gensim 4.0.0.

    AttributeError: The vocab attribute was removed from KeyedVector in Gensim 4.0.0.

    Use KeyedVector's .key_to_index dict, .index_to_key list, and methods .get_vecattr(key, attr) and .set_vecattr(key, attr, new_val) instead.

    opened by AI-Ahmed 1
  • Erorr in seminar01/backprop/adaptive_sgd

    Erorr in seminar01/backprop/adaptive_sgd

    Some cells in seminar01/backprop/adaptive_sgd/adaptive_sgd.ipynb contains visualize(X[ind,:], y[ind], w, loss, n_iter) instead of visualize(X[ind,:], y[ind], w, loss). The first one should be replaced with the second one.

    opened by AlekseySh 0
  • week08:autoencoders_pytorch Pooling layers usage

    week08:autoencoders_pytorch Pooling layers usage

    MaxUnpool needs "indices" that are returned by MaxPool but the first is located in the decoder and the second is in the encoder thus all direct calls of starter code to encoder and decoder do not support the indices transportation from Pool to Unpool

    Possible solutions:

    1. do not use direct calls for counting code/reconstruction
    2. request both code and reconstruction using one function call
    opened by NickVeld 0
Owner
Yandex School of Data Analysis
Yandex School of Data Analysis
GitHub
All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

Daniel Bourke 3.4k Jan 7, 2023
PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to handle and build

simple, elegant and safe Introduction PassAPI is a password generator in hash format and fully developed in Python, with the aim of teaching how to ha

Johnsz 2 Mar 2, 2022
An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.

SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow

Zhihu 44 Oct 20, 2022
This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!

Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev

Popstar Idhant 3 Feb 25, 2022
Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*

Developed an optimized algorithm which finds the most optimal path between 2 points in a 3D Maze using various AI search techniques like BFS, DFS, UCS, Greedy BFS and A*. The algorithm was extremely optimal running in ~15s to ~30s for search spaces as big as 10000000 nodes where a set of 18 actions could be performed at each node in the 3D Maze.

null 1 Mar 28, 2022
Repository for the electrical and ICT benchmark model developed in the ERIGrid 2.0 project.

Benchmark Model Electrical and ICT System This repository contains the documentation, code, and models for the electrical and ICT benchmark model deve

ERIGrid 2.0 1 Nov 29, 2021
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

Blue Collar Bioinformatics 917 Jan 3, 2023
Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Patient-Survival - Using Python, I developed a Machine Learning model using classification techniques such as Random Forest and SVM classifiers to predict a patient's survival status that have undergone breast cancer surgery.

Nafis Ahmed 1 Dec 28, 2021
RITA is a family of autoregressive protein models, developed by LightOn in collaboration with the OATML group at Oxford and the Debora Marks Lab at Harvard.

RITA: a Study on Scaling Up Generative Protein Sequence Models RITA is a family of autoregressive protein models, developed by a collaboration of Ligh

LightOn 69 Dec 22, 2022
python-timbl, originally developed by Sander Canisius, is a Python extension module wrapping the full TiMBL C++ programming interface. With this module, all functionality exposed through the C++ interface is also available to Python scripts. Being able to access the API from Python greatly facilitates prototyping TiMBL-based applications.

README: python-timbl Authors: Sander Canisius, Maarten van Gompel Contact: [email protected] Web site: https://github.com/proycon/python-timbl/ pytho

Maarten van Gompel 16 Jan 16, 2022
This repo is developed for Strong Baseline For Vehicle Re-Identification in Track 2 Ai-City-2021 Challenges

A STRONG BASELINE FOR VEHICLE RE-IDENTIFICATION This paper is accepted to the IEEE Conference on Computer Vision and Pattern Recognition Workshop(CVPR

Cybercore Co. Ltd 78 Dec 29, 2022
Repository for publicly available deep learning models developed in Rosetta community

trRosetta2 This package contains deep learning models and related scripts used by Baker group in CASP14. Installation Linux/Mac clone the package git

null 81 Dec 29, 2022
A trusty face recognition research platform developed by Tencent Youtu Lab

Introduction TFace: A trusty face recognition research platform developed by Tencent Youtu Lab. It provides a high-performance distributed training fr

Tencent 956 Jan 1, 2023
PERIN is Permutation-Invariant Semantic Parser developed for MRP 2020

PERIN: Permutation-invariant Semantic Parsing David Samuel & Milan Straka Charles University Faculty of Mathematics and Physics Institute of Formal an

ÚFAL 40 Jan 4, 2023
Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim

Viet Nguyen 89 Dec 18, 2022
A big endian Gentoo port developed on a Pine64.org RockPro64

Gentoo-aarch64_be A big endian Gentoo port developed on a Pine64.org RockPro64 The endian wars are over... little endian won. As a result, it is incre

Rory Bolt 6 Dec 7, 2022
TUPÃ was developed to analyze electric field properties in molecular simulations

TUPÃ: Electric field analyses for molecular simulations What is TUPÃ? TUPÃ (pronounced as tu-pan) is a python algorithm that employs MDAnalysis engine

Marcelo D. Polêto 10 Jul 17, 2022
Bot developed in Python that automates races in pegaxy.

español | português About it: This is a fork from pega-racing-bot. This bot, developed in Python, is to automate races in pegaxy. The game developers

null 4 Apr 8, 2022
A platform for intelligent agent learning based on a 3D open-world FPS game developed by Inspir.AI.

Wilderness Scavenger: 3D Open-World FPS Game AI Challenge This is a platform for intelligent agent learning based on a 3D open-world FPS game develope

null 46 Nov 24, 2022