Resources complimenting the Machine Learning Course led in the Faculty of mathematics and informatics part of Sofia University.

Related tags

Deep Learningpythondata-sciencemachine-learningdeep-learningtensorflownumpyscikit-learnsklearnpandaspython3matplotlib
Overview

Machine Learning and Data Mining, Summer 2021-2022

How to learn data science and machine learning?

  1. Programming. Learn Python.
  2. Basic Statistics. Take a look at the amazing YouTube channel in the Maths section.
  3. Databases. Learn SQL. Check out mode.com.
  4. Exploratory Data Analysis. Learn how to work with NumPy, Pandas, Matplotlib, Seaborn.
  5. Machine Learning. Learn the various algorithms. Explore Scikit learn.
  6. Data scraping. Explore the Beautiful soup library.
  7. Study the niches: deep learning, nlp (natural language processing), cv (computer vision).
  8. Deployment. Explore Flask, Streamlit, Django.

Framework

  1. Learn just enough.
  2. Do a project. For example choose one from Kaggle.
  3. Iterate.
  4. Accountability. Show off your work on Github.

Most important APIs

Resources

Python

Markdown

Maths

Machine learning and Deep learning

Books

Owner
Simeon Hristov
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Simeon Hristov
GitHub Repository
This is a simple face recognition mini project that was completed by a team of 3 members in 1 week's time

PeekingDuckling 1. Description This is an implementation of facial identification algorithm to detect and identify the faces of the 3 team members Cla

Eric Kwok 2 Jan 25, 2022
An official implementation of MobileStyleGAN in PyTorch

MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis Official PyTorch Implementation The accompanying videos c

Sergei Belousov 602 Jan 07, 2023
Pytorch implementation for M^3L

Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification (CVPR 2021) Introduction This is the Py

Yuyang Zhao 45 Dec 26, 2022
The code for the NSDI'21 paper "BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing".

BMC The code for the NSDI'21 paper "BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing". BibTex entry available here. B

Orange 383 Dec 16, 2022
A SAT-based sudoku solver

SAT Sudoku solver A SAT-based Sudoku solver made in the context of a small project in the "Logic Problem Solving" class in the first year at the Polyt

Alexandre Malfreyt 5 Apr 15, 2022
A library for finding knowledge neurons in pretrained transformer models.

knowledge-neurons An open source repository replicating the 2021 paper Knowledge Neurons in Pretrained Transformers by Dai et al., and extending the t

EleutherAI 96 Dec 21, 2022
Repository for benchmarking graph neural networks

Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files

NTU Graph Deep Learning Lab 2k Jan 03, 2023
ReSSL: Relational Self-Supervised Learning with Weak Augmentation

ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model

mingkai 45 Oct 25, 2022
Adaptive Graph Convolution for Point Cloud Analysis

Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph

64 Dec 21, 2022
Augmented CLIP - Training simple models to predict CLIP image embeddings from text embeddings, and vice versa.

Train aug_clip against laion400m-embeddings found here: https://laion.ai/laion-400-open-dataset/ - note that this used the base ViT-B/32 CLIP model. S

Peter Baylies 55 Sep 13, 2022
FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics

FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt

Choi Gunho 102 Dec 13, 2022
Spectralformer: Rethinking hyperspectral image classification with transformers

Spectralformer: Rethinking hyperspectral image classification with transformers Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza

Danfeng Hong 102 Dec 29, 2022
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int

CVMI Lab 228 Dec 25, 2022
The official repository for "Score Transformer: Generating Musical Scores from Note-level Representation" (MMAsia '21)

Score Transformer This is the official repository for "Score Transformer": Score Transformer: Generating Musical Scores from Note-level Representation

22 Dec 22, 2022
[Preprint] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora

VITA 64 Dec 08, 2022
An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi

MetaICL: Learning to Learn In Context This includes an original implementation of "MetaICL: Learning to Learn In Context" by Sewon Min, Mike Lewis, Lu

Meta Research 141 Jan 07, 2023
Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs

Perceiver IO Unofficial implementation of Perceiver IO: A General Architecture for Structured Inputs & Outputs Usage import torch from src.perceiver.

Timur Ganiev 111 Nov 15, 2022
[NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A

Hanxun Huang 26 Dec 01, 2022
PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC

DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC

Kazuto Nakashima 995 Jan 08, 2023
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r

RGF-team 364 Dec 28, 2022