omerbsezer

This repo covers Kubernetes with LABs: Kubectl, Pod, Deployment, Service, PV, PVC, Rollout, Multicontainer, Daemonset, Taint-Toleration, Job, Ingress, Kubeadm, Helm, etc.

LSTM-RNN Tutorial with LSTM and RNN Tutorial with Demo with Demo Projects such as Stock/Bitcoin Time Series Prediction, Sentiment Analysis, Music Generation using Keras-Tensorflow

Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning,...

This repo covers containerization and Docker Environment: Docker File, Image, Container, Commands, Volumes, Networks, Swarm, Stack, Service, possible scenarios.

This repo covers Ansible with LABs: Multipass, Commands, Modules, Playbooks, Tags, Managing Files and Servers, Users, Roles, Handlers, Host Variables, Templates and details.

Pytorch Tutorial, Pytorch with Google Colab, Pytorch Implementations: CNN, RNN, DCGAN, Transfer Learning, Chatbot, Pytorch Sample Codes

This repo covers Terraform (Infrastructure as Code) with LABs using AWS and AWS Sample Projects: Resources, Variables, Meta Arguments, Provisioners, Dynamic Blocks, Modules, Provisioning AWS...

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models,...

Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach: A novel algorithmic trading model CNN-TA using a 2-D convolutional neural network...

This repo covers Kubeflow Environment with LABs: Kubeflow GUI, Jupyter Notebooks on pods, Kubeflow Pipelines, Experiments, KALE, KATIB (AutoML: Hyperparameter Tuning), KFServe (Model Serving),...

This repo covers LLM, Agents, MCP Tools, Skills concepts with sample codes: LangChain & LangGraph, AWS Strands Agents, Google Agent Development Kit, Fundamentals.

This repo covers AWS Hands-on Labs for different AWS services

A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)