You will get an image dataset for training ML models.
Project details
Curated image datasets sourced from our petabyte-scale database of billions of images
Designed for advanced AI and ML research. Datasets include pre-split partitions for seamless integration into training, validation, and testing workflows.
Additional features: detailed annotations and comprehensive metadata (EXIF data, similarity scores, captions). Contact for vision-based labeling (e.g., bounding boxes, facial landmarks, pose estimation).
Designed for advanced AI and ML research. Datasets include pre-split partitions for seamless integration into training, validation, and testing workflows.
Additional features: detailed annotations and comprehensive metadata (EXIF data, similarity scores, captions). Contact for vision-based labeling (e.g., bounding boxes, facial landmarks, pose estimation).
AI Algorithms
Convolutional Neural Network, Generative Adversarial Network, Large Language Model, StyleGAN, Transformer Model, YOLOAI Applications
AI Text-to-Image, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Video, Image Processing, Image Recognition, Neural Style Transfer, Object Detection, Object Localization, Synthetic Data GenerationAI Development Language
PythonAI Tools
Hugging Face, NVIDIA AI Platform, PyTorchAI Models
ChatGPT, GPT-4, Midjourney AI, Stable DiffusionWhat's included $300
These options are included with the project scope.
$300
- Delivery Time 3 days
Optional add-ons
You can add these on the next page.
Fast 1 Day Delivery
+$200Frequently asked questions
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DF
David F.
Nov 2, 2022
OpenAI GPT-3 Application Development
John was an 11/10 -- super helpful and knowledgable to work with. Great work ethic, would 100% hire again!
SK
Sasha K.
Mar 1, 2022
Chrome extension linked to GPT-3 API
John did a phenomenal job. He went above and beyond and I'm very pleased with the end result. He's extremely skilled and very punctual. And a great guy to work with :)!
About John
ML Engineer - Transformers, LLMs
Palo Alto, United States - 9:10 am local time
- Large-scale language model pre-training and fine-tuning.
- Software architecture and system design.
- Semantic search (training embedding models, ANN/HNSW, billions-scale dataset ingestion, vectorization, and optimization).
- Implementation of research into full-featured codebases, such as novel self-attention mechanisms, hyperparameter tuning, implementing custom loss functions.
- ML infrastructure (distributed deployment, data pipelines, process management of very large generative models).
- Computer vision, object recognition models such as convolutional neural networks, recurrent neural networks, U-Net, and image processing with OpenCV.
- Deep learning libraries (PyTorch, TensorFlow, Keras).
- Training text-to-image diffusion models (Stable Diffusion, DeepFloyd) and multimodal transformers.
- LLM-driven code generation with reinforcement learning.
- Prompt engineering (chain of thought, tree of thoughts, retrieval-augmented generation, self-reflection).
- Data labeling tool design (custom front-end UIs, Gradio).
- Python data science tools (Pandas, Seaborn, Matplotlib).
- Data visualization.
- Data acquisition/scraping, data cleaning, deduping.
- Huggingface datasets, models, Inference API, transformers & diffusers libraries.
- Web development (Python, FastAPI, Flask/Django, Javascript, jQuery).
Steps for completing your project
After purchasing the project, send requirements so John can start the project.
Delivery time starts when John receives requirements from you.
John works on your project following the steps below.
Revisions may occur after the delivery date.
Client Consultation
Set up a meeting to discuss project requirements, including any additional services (computationally intensive tasks, custom requirements, etc.)
Data Aggregation
Compile images from our database, organized to align with specific project requirements.