30 days of JavaScript programming challenge is a step-by-step guide to learn JavaScript programming language in 30 days. This challenge may take more than 100 days, please just follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
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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, AWS, and various command lines.
30 Days of React challenge is a step by step guide to learn React in 30 days. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
- challenge
- javascript
- js
- react
🛠️⚡ Step-by-step tutorial to build a modern JavaScript stack.
TranslatedAn easy-to-understand, witty and humorous Java learning guide, covering core knowledge points such as Java basics, Java concurrent programming, the Java Virtual Machine, Java enterprise development, and Java interviews. To learn Java, look no further than 二哥's (Erge, "Second Brother") Java advancement path 😄
- java
- jvm
- springboot
- mysql
TranslatedBig Data Beginner's Guide :star:
- hadoop
- hdfs
- yarn
- mapreduce
TranslatedSpring Boot practical learning examples, the best practice for Spring Boot beginners and for consolidating core technologies.
- springboot
- redis
- jpa
- elasticsearch
Translated"Spring Boot Basic Tutorial", the 2.x version is being published serially and is still ongoing! Click the link below to go straight to the tutorial table of contents!
- spring-boot
- spring-cloud
- spring-data-jpa
- dubbo
Translatedflink learning blog. http://www.54tianzhisheng.cn/ Covers Flink introduction, concepts, principles, hands-on practice, performance tuning, source code analysis, and more. Includes learning examples involving Flink Connector, Metrics, Library, DataStream API, Table API & SQL, and also shares large-scale project cases of Flink in production (PV/UV, log storage, real-time deduplication of 10 billion records, monitoring and alerting). You are welcome to support my column 《大数据实时计算引擎 Flink 实战与性能优化》 ("Big Data Real-Time Computing Engine Flink: Hands-On Practice and Performance Optimization")
Translatedmall learning tutorial, with a comprehensive analysis of the architecture, business logic, and key technical points. The mall project (60k+ stars) is an e-commerce system built with currently mainstream technologies. It covers technologies such as SpringBoot, MyBatis, Elasticsearch, RabbitMQ, Redis, MongoDB, and MySQL, and uses Docker containerized deployment.
- springboot
- mybatis
- elasticsearch
- rabbitmq
The complete guide to static typing in "React & Redux" apps using TypeScript
This guide details creating a secure Linux production system. OpenSCAP (C2S/CIS, STIG).
This repository has examples of broken patterns in ASP.NET Core applications
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.
Inspired by @veltman's command-line mystery, use SQL to research clues and find out whodunit!
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
- seq2seq
- tensorflow
- tensorflow-tutorials
- python
Train and Deploy an ML REST API to predict crypto prices, in 10 steps
WebGPU tutorials inspired by LearningWebGL.com. Use both WGSL and GLSL/SPIR-V.
- webgpu
- wgsl