Chooch
Visionify.ai
Clarifai
Oxagile IoT Services
Google Vision AI
Amazon Rekognition
InData Labs
OpenCV
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
Exploratory
htm.java
Chooch's Generative AI-powered computer vision technology enables businesses to leverage their existing camera and image data for real-time insights, empowering more proactive decision-making. It streamlines manual visual review tasks, enhancing operational efficiency, optimizing human resource allocation, and ultimately reducing costs.
Chooch AI Vision technology identifies patterns, objects, and actions within video data and images, promptly recognizing their significance and triggering alerts to initiate further action. Using existing cameras and edge infrastructure, Chooch facilitates the deployment of AI models to analyze vast amounts of data within video streams, accomplishing pre-determined detections in a fraction of the time required by human operators.
The platform offers a comprehensive suite of services covering the entire machine learning AI workflow, including data augmentation tools, model training and hosting, edge device deployment, real-time inferencing, and intelligent analytics.
Chooch empowers organizations to rapidly deploy AI Vision across their camera infrastructure using pre-trained models tailored to various use cases, addressing a wide array of business challenges such as workplace safety, retail loss prevention, people counting, inventory management, wildfire detection, and more. With Chooch's AI-powered computer vision solutions, businesses can efficiently manage visual data at scale, detecting, understanding, and responding instantly to critical events.
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Chooch’s AI Vision technology combines computer vision and language understanding to deliver generative AI for image-to-text.
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Chooch was founded by Turkish-American brothers, business focused, Emrah, and technology driven, Hakan Gültekin. Emrah, a serial entrepreneur, had spent 20 years building startups and businesses from an engineering consultancy, to real estate development, to commercial and social investment consulting. He saw the world was rapidly changing and not exactly in the right direction. Despite technological advancements, there continued to be a lack of efficiency, foresight, and transparency to help companies make the right decisions, and he had a strong desire to contribute to the next wave of technological innovation to solve this. Chooch was founded at the intersection of the evolution of society and the advancement of artificial intelligence.
Based on our record, Scikit-learn seems to be more popular. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 12 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
Visionify.ai - Specialized Computer Vision solutions provider
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Clarifai - The World's AI
OpenCV - OpenCV is the world's biggest computer vision library
Oxagile IoT Services - Leverage our IT consulting services to foster enterprise-grade optimization, accelerate digital transformation, and drive exceptional customer value.
NumPy - NumPy is the fundamental package for scientific computing with Python