Pinned Repositories
ai-baselines
ai-baselines is a Reinforcement Learning platform for Swift ecosystem targeting AI researchers. It connects to Unity environment via gRPC and allows you to train baseline TensorFlow models.
atadanicen
atadanicen.github.io
This is my personal website, and I welcome you to get in touch with me at your convenience. Please feel free to reach out anytime.
currency-minds
Currency Minds is a simple yet powerful currency converter and time series data visualization tool.
file-organizer
This Python script is designed to organize files in the Downloads directory by automatically moving them to specific folders based on their file extensions
get-started
Ollama Cloud is a Highly Scalable Cloud-native Stack for Ollama
Learn-Keras-for-Deep-Neural-Networks
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.
Neo-nearEarthObservation
This app aims to simplify the usage of Nasa Public API for who wanna observe asteroids approaching to the Earth.
realistic-photo-generator
AI-driven photo-generator app featuring IP-Face Adapter technology. Create personalized images with your own face effortlessly!
travel-planner
The AI Travel Planner app allows users to effortlessly create personalized travel itineraries based on their destination, travel dates, and interests. By inputting these key details, the app leverages advanced AI agents to curate customized recommendations and suggestions for an enriching travel experience.
atadanicen's Repositories
atadanicen/realistic-photo-generator
AI-driven photo-generator app featuring IP-Face Adapter technology. Create personalized images with your own face effortlessly!
atadanicen/travel-planner
The AI Travel Planner app allows users to effortlessly create personalized travel itineraries based on their destination, travel dates, and interests. By inputting these key details, the app leverages advanced AI agents to curate customized recommendations and suggestions for an enriching travel experience.
atadanicen/Neo-nearEarthObservation
This app aims to simplify the usage of Nasa Public API for who wanna observe asteroids approaching to the Earth.
atadanicen/ai-baselines
ai-baselines is a Reinforcement Learning platform for Swift ecosystem targeting AI researchers. It connects to Unity environment via gRPC and allows you to train baseline TensorFlow models.
atadanicen/Learn-Keras-for-Deep-Neural-Networks
Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras. The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.
atadanicen/atadanicen
atadanicen/atadanicen.github.io
This is my personal website, and I welcome you to get in touch with me at your convenience. Please feel free to reach out anytime.
atadanicen/currency-minds
Currency Minds is a simple yet powerful currency converter and time series data visualization tool.
atadanicen/file-organizer
This Python script is designed to organize files in the Downloads directory by automatically moving them to specific folders based on their file extensions
atadanicen/get-started
Ollama Cloud is a Highly Scalable Cloud-native Stack for Ollama
atadanicen/hetzner-k3s
The easiest and quickest way to create and manage Kubernetes clusters in Hetzner Cloud using the lightweight distribution k3s by Rancher.
atadanicen/lightning-ai-rds
Lightning AI RDS (Remote Development Server) Repository
atadanicen/Web-Application-Development-with-Streamlit
source code