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A curated list of free courses & certifications.
Decoupling Reasoning from Observations for Efficient Augmented Language Models
A highly efficient implementation of Gaussian Processes in PyTorch
MongoDB data stream pipeline tools by YouGov (adopted from MongoDB)
📚 A curated list of papers for Software Engineers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Extract highlights, underlines and annotations from your PDFs into Obsidian
Extracts and formats text annotations from a PDF file
A curated list of awesome Machine Learning frameworks, libraries and software.
An opinionated list of awesome Python frameworks, libraries, software and resources.
Python library for converting Python calculations into rendered latex.
Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
The new Windows Terminal and the original Windows console host, all in the same place!
Hierarchical perception library in Python for pose estimation, object detection, instance segmentation, keypoint estimation, face recognition, etc.
An open source library for face detection in images. The face detection speed can reach 1000FPS.
Short Python code snippets for all your development needs
To build a gender, race and age detector that can approximately guess the gender, race and age of the person (face) in a picture.
Windows system utilities to maximize productivity
In my computer security courses I make extensive usage of cheatsheets for various tools and extra materials to complement the student learning if they are willing to do so. I have decided to share …
Subreddit analysis of posts and users
PyTorch implementation of neural style transfer algorithm
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Lab Materials for MIT 6.S191: Introduction to Deep Learning