Hidden Brains offers the deepest and broadest set of Machine Learning and Artificial Intelligence consulting services, putting the power of machine learning in the hands of every developer, data scientist and expert practitioner. We are the pioneers in AI solution and implementation services. Hidden Brains is helping customers accelerate their machine learning and artificial intelligence journey.
Our AI support services provide ready-made intelligence for your applications and workflows. Artificial Intelligence software solutions easily integrate with your applications to address common use cases such as personalized recommendations, modernizing your contact center, improving safety and security, and increasing customer engagement.
Choose from TensorFlow, PyTorch, ONNX, and other popular frameworks to experiment with and customize machine learning algorithms.
TensorFlow comes with a full suite of visualization tools that make it easy to understand, debug, and optimize applications.
ONNX defines the format for the neural network's computational graph, as well as the format for an extensive list of operators used within the graph.
An open source machine learning framework that accelerates the path from research prototyping to production deployment. It is ‘production-ready’ and has a robust ecosystem.
Keras is an open-source neural-network library written in Python. It is capable of running on top of TensorFlow. Keras is an API designed for human beings, not machines.
Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs.
A fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly.
Our Azure Machine Learning consulting and deployment can be used for any kind of machine learning, from classical ML to deep learning, supervised, and unsupervised learning.
The perfect comprehensive toolkit for quickly developing applications and solutions that emulate human vision.
We help you develop, test, and run your workloads for free on a cluster of the latest Intel® hardware and software.
Interactive dashboards and visualizations in real time to create visualizations in an effort to solve complex problems and track it. We analyze all the information regarding business and make definite data-driven decisions.
Our data & analytics expertise delivers business value to software companies trying to infuse data science within products, and to enterprises attempting to uncover data-driven decisions.
With statistical techniques from data mining, predictive modelling, and machine learning one can analyze historical data.
Experience in creating “Content Based Recommendation” and “Collaborative Recommendation Engine” to analyse historical data, user patterns and behavior to predict and make recommendations.
Forecasting approaches including qualitative models and quantitative models that help you gather significant insights.
Our NLP software solutions combine ML, AI, and advanced technologies to allow machines to read human language with products such as “FAQ Help Desk”, “ChatBot” and more.
With image processing libraries, we create custom convolutional neural network (CNN) models to provide highly scalable and robust deep learning solutions to our customers.
We collaborate with businesses to deploy their own personalized voice-based assistants to assist customers and keep them engaged.
We use sentimental Analysis to analyze sentiments and intent of customers and gather emails, social media queries, customer forms to derive important conclusions from that data.
Our clients across the globe recognize our persistence to deliver industry-focused technology solutions, as well as our flexible processes.
Get all your questions answered before hiring the right resource
All of these frameworks have their own strengths and weaknesses. Some are better for computer vision applications while others are better for natural language processing.
We find that the best way to decide which framework is best is to start by understanding your problem space as well as your engineering team's skillset.
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