Class materials for a distributed systems lecture series
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The Concise TypeScript Book: A Concise Guide to Effective Development in TypeScript. Free and Open Source.
- book
- learn-typescript
- typescript
- typescript-book
Techniques for deep learning with satellite & aerial imagery
- deep-learning
- deep-neural-networks
- satellite-imagery
- pytorch
TensorFlow Tutorials with YouTube Videos
TensorFlow tutorials and best practices.
🗡️ Pokedex demonstrates modern Android development with Hilt, Material Motion, Coroutines, Flow, Jetpack (Room, ViewModel) based on MVVM architecture.
- android
- kotlin
- pokemon
- pokedex
An awesome list of awesome YouTubers that teach about technology. Tutorials about web development, computer science, machine learning, game development, cybersecurity, and more.
- awesome
- awesome-list
- list
- youtubers
Toturials coming with the "data science roadmap" picture.
[Examples] Simple basic isolated apps, for budding flutter devs.
Step-by-step guide through the abstract and complex universe of Fragment Shaders.
A free, online learning platform to make quality education accessible for all.
Kubernetes application example tutorials
A course in reinforcement learning in the wild
- reinforcement-learning
- course-materials
- deep-learning
- deep-reinforcement-learning
Roadmap to becoming an iOS developer in 2018.
- swift
- ios
- objective-c
- architecture
:dolphin: A comprehensive tutorial on getting started with Docker!
- docker
- tutorials
- cloud-computing
- microservices
Course materials for Modern Binary Exploitation by RPISEC
- exploitation
- wargame
- ctf
Simple tutorials using Google's TensorFlow Framework
A curated list of fuzzing resources ( Books, courses - free and paid, videos, tools, tutorials and vulnerable applications to practice on ) for learning Fuzzing and initial phases of Exploit Development like root cause analysis.
- awesome-list
- awesome
- fuzzing
- fuzzing-framework
common data analysis and machine learning tasks using python
- data-science
- python
- python-tutorial
- data-scientists
From the basics to slightly more interesting applications of Tensorflow
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
A collection of AWESOME things about domain adaptation
- transfer-learning
- domain-adaptation
- adversarial-learning
- image-translation
One stop solution for all Vulkan samples
Promise packages, patterns, chat, and tutorials
- async-functions
- promise-modules
- promises
- javascript