CSTR-Edinburgh / Mlpractical
Licence: bsd-3-clause
Machine Learning Practical course repository
Stars: ✭ 295
Projects that are alternatives of or similar to Mlpractical
Tcdf
Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
Stars: ✭ 217 (-26.44%)
Mutual labels: jupyter-notebook, neural-networks
Neural Network From Scratch
Ever wondered how to code your Neural Network using NumPy, with no frameworks involved?
Stars: ✭ 230 (-22.03%)
Mutual labels: jupyter-notebook, neural-networks
Pixel level land classification
Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.
Stars: ✭ 217 (-26.44%)
Mutual labels: jupyter-notebook, neural-networks
Unsupervisedscalablerepresentationlearningtimeseries
Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments
Stars: ✭ 205 (-30.51%)
Mutual labels: jupyter-notebook, neural-networks
Graph Based Deep Learning Literature
links to conference publications in graph-based deep learning
Stars: ✭ 3,428 (+1062.03%)
Mutual labels: jupyter-notebook, neural-networks
Gluon Api
A clear, concise, simple yet powerful and efficient API for deep learning.
Stars: ✭ 2,322 (+687.12%)
Mutual labels: jupyter-notebook, neural-networks
Mydatascienceportfolio
Applying Data Science and Machine Learning to Solve Real World Business Problems
Stars: ✭ 227 (-23.05%)
Mutual labels: jupyter-notebook, neural-networks
Deep Learning Notes
My personal notes, presentations, and notebooks on everything Deep Learning.
Stars: ✭ 191 (-35.25%)
Mutual labels: jupyter-notebook, neural-networks
Deeplearning.ai Notes
These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.
Stars: ✭ 262 (-11.19%)
Mutual labels: jupyter-notebook, neural-networks
Place Recognition Using Autoencoders And Nn
Place recognition with WiFi fingerprints using Autoencoders and Neural Networks
Stars: ✭ 256 (-13.22%)
Mutual labels: jupyter-notebook, neural-networks
Radio
RadIO is a library for data science research of computed tomography imaging
Stars: ✭ 198 (-32.88%)
Mutual labels: jupyter-notebook, neural-networks
Deep Learning With Python
Deep learning codes and projects using Python
Stars: ✭ 195 (-33.9%)
Mutual labels: jupyter-notebook, neural-networks
Tutorials
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Stars: ✭ 204 (-30.85%)
Mutual labels: jupyter-notebook, neural-networks
Coursera Deep Learning Specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Stars: ✭ 188 (-36.27%)
Mutual labels: jupyter-notebook, neural-networks
Machine Learning Notebooks
Machine Learning notebooks for refreshing concepts.
Stars: ✭ 222 (-24.75%)
Mutual labels: jupyter-notebook, neural-networks
Attentionn
All about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.
Stars: ✭ 175 (-40.68%)
Mutual labels: jupyter-notebook, neural-networks
Lstm anomaly thesis
Anomaly detection for temporal data using LSTMs
Stars: ✭ 178 (-39.66%)
Mutual labels: jupyter-notebook, neural-networks
Nn
🧑🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Stars: ✭ 5,720 (+1838.98%)
Mutual labels: jupyter-notebook, neural-networks
Deeplearning Challenges
Codes for weekly challenges on Deep Learning by Siraj
Stars: ✭ 264 (-10.51%)
Mutual labels: jupyter-notebook, neural-networks
Machine Learning Practical
This repository contains the code for the University of Edinburgh School of Informatics course Machine Learning Practical.
This assignment-based course is focused on the implementation and evaluation of machine learning systems. Students who do this course will have experience in the design, implementation, training, and evaluation of machine learning systems.
The code in this repository is split into:
- a Python package
mlp, a NumPy based neural network package designed specifically for the course that students will implement parts of and extend during the course labs and assignments, - a series of Jupyter notebooks in the
notebooksdirectory containing explanatory material and coding exercises to be completed during the course labs.
Getting set up
Detailed instructions for setting up a development environment for the course are given in this file. Students doing the course will spend part of the first lab getting their own environment set up.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].