Ömer Berat Sezer

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

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

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

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

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

Fast-Terraform. 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 Resources (EC2, EBS, EFS, VPC, IAM Policies, Roles, ECS, ECR, Fargate, EKS, Lambda, API-Gateway, ELB, S3, etc.

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

CNN-TA. 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 based on image processing properties.

Fast-Kubeflow. This repo covers Kubeflow Environment with LABs: Kubeflow GUI, Jupyter Notebooks on pods, Kubeflow Pipelines, Experiments, KALE, KATIB (AutoML: Hyperparameter Tuning), KFServe (Model Serving), Training Operators (Distributed Training), Projects, etc.

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

SparkDeepMlpGADow30. A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)

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

TimeSeries2DBarChartImageCNN. Conversion of the time series values to 2-D stock bar chart images and prediction using CNN (using Keras-Tensorflow)

SparkMlpDow30. A new stock trading and prediction model based on a MLP neural network utilizing technical analysis indicator values as features (using Apache Spark MLlib)

AIMap. Map of Artificial Intelligence: Classifications, Approaches, Algorithms, Libraries, Tools, State of Art Studies, Awesome Repos, etc..

PolicyGradient_PongGame. Pong Game problem solving using RL - Policy Gradient with OpenAI Gym Framework and Tensorflow

Qlearning_MountainCar. Mountain Car problem solving using RL - QLearning with OpenAI Gym Framework

ml-monitoring. A demo of Prometheus+Grafana for monitoring an ML model served with FastAPI.

NeuralStyleTransfer. Art/Painting Generation using AI (Neural Style Transfer) using Tensorflow

AI-Content-Detector. Tool to give AI generated score, to analyze with patterns how much input text is AI generated using AWS Bedrock Llama 3.1 405B

BasicLSTM. The aim of this implementation is to help to learn structure of basic LSTM (LSTM cell forward, LSTM cell backward, etc..)

IoTSmartHomeOntologySimulator. A smart home sensor ontology (that is a specialized ontology based on the Semantic Sensor Networks (SSN) ontology) and simulation evironment of a smart home use case

SentimentAnalysis. Sentences are classified in 5 different sentiment using LSTM (Keras). Results are expressed with emoji characters.

IoTWeatherSensorsAnalysis. Proposed "An Extended IoT Framework" learning part is presented with a use case on weather data clustering analysis. Sensor faults and anomalies are determined using K-means clustering (using scikit-learn)

MusicGeneration. Music generation with LSTM model (Keras)

MCP-Agent-Ollama. MCP-Agent-Ollama

modelbuild_pipeline. Test Repo for Model Build

omerbsezer.

QLearning_CartPole. Cart Pole problem solving using RL - QLearning with OpenAI Gym Framework

modeldeploy_pipeline. Test Repo for Model Deploy

BasicRNN. The aim of this implementation is to help to learn structure of basic RNN (RNN cell forward, RNN cell backward, etc..)