nagask's repositories
appdocs
Application Performance Optimization Summary
awesome-flink
😎 A curated list of amazingly awesome Flink and Flink ecosystem resources
beamexample
An example Apache Beam project.
cheatsheets-ai
Essential Cheat Sheets for deep learning and machine learning researchers
CISCO_Share
Core Java Material
cloud-native-slides-share
Cloud Native slides and materials share
data-dev-learning-labs
Source for the Cisco DevNet Data Developer learning labs
data-engineering-gcp
Data Engineering on Google Cloud Platform
data_engineer_test
Test assignment for job interview. Processes multiple different types of data files
deep_recommend_system
TensorFlow template application for deep learning
e-commerce-microservices-sample
A fictitious cloud-native e-commerce application using micro-services architecture powered by Spring Cloud, Docker
flink-spector
Framework for Apache Flink unit tests
flink-stream-processing-refarch
Reference architecture for real-time stream processing with Apache Flink on Amazon EMR, Amazon Kinesis, and Amazon Elasticsearch Service.
gcp
GCP: Complete Google Data Engineer and Cloud Architect
GCP-data-engineer-training-course
Notes for the data engineering training on Google Cloud Platform
Google Interview Prep
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
kubernetes
Production-Grade Container Scheduling and Management
machine-learning-cheat-sheet
Classical equations and diagrams in machine learning
ml
Machine Learning Notes
neural-networks-and-deep-learning
Code samples for my book "Neural Networks and Deep Learning"
PRML
PRML algorithms implemented in Python
sql-challenges
Solutions to SQL problems
SQL-exercise
Practice with "Real" SQL Problems
stats337
Readings in applied data science
stream-reactor
Streaming reference architecture built around Kafka.
tensorflow-mnist-tutorial
Sample code for "Tensorflow and deep learning, without a PhD" presentation and code lab.
workshop-2017-10
Some lessons learned from processing FB data.