Grow your business with machine learning services
Enterprise-grade machine learning service to build and deploy models faster. Gain a competitive edge with highly customized & scalable machine learning solutions
Sofstack Machine Learning Services
Our machine learning services help you in Innovative machine learning products and services, to manage production machine learning workflows at scale in an enterprise-ready with help of predictive analytics, data transformations and visualizations, data modelling APIs, facial recognition, natural language processing and machine deep learning algorithms. By using Machine Learning services businesses are able to improve their product capabilities and offerings, make regular business operations more efficient, interaction with customers easier and use AI prediction capabilities to create more precise business strategies.
Since working with enterprises is not implementing one time the best solutions and only doing what is being asked to do, but propose improvements and functionalities that are so much better suited to create new opportunities.
The model building process involves setting up ways of collecting data, understanding and paying attention to what is important in the data to answer the questions you are asking, finding a statistical, mathematical or a simulation model to gain understanding and make predictions.The three stages on which sofstack build the hypotheses in machine learning are model building, model testing and applying model.
Predictive analytics uses many techniques from data mining, statistics, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future. Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events.
Natural Language Processing
Natural language processing is a branch of artificial intelligence that helps computers to understand , interpret & manipulate human language. Sofstack provides the following natural language processing application.Document
summarization, Language identification,
Sentiment analysis, Text classification,
Named entity recognition, Machine translation
Computer Vision service offerings for Image Analytics, Text Analytics, Video Analytics, Face Detection and Recognition. We will integrate computer vision services in your product or service. With a customized approach, our Computer Vision developers work will train and deploy models to identify specific places, people, and objects and categorize them to retrieve valuable information as well as analytics.
Step on the Neutral networks / deep learning path with our Machine Learning developers, engineers and consultants perfectly suited to your needs. Neutral Networks is one way of implementing machine learning (automated data analysis) via artificial neural networks — algorithms that effectively mimic the human brain’s structure and function.
A chatbot is a computer program that's designed to simulate human conversation. Users communicate with these tools using a chat interface or via voice, just like they would converse with another person. Chatbots interpret the words given to them by a person and provide a pre-set answer.
Data visualization is an interdisciplinary field that deals with the graphic representation of data. Sofstack helps By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.
Big Data Analytics
Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to dealt with.Big data analytics is the use of advanced analytic techniques against very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources, and in different sizes from terabytes to zettabytes.
Deployment of an ML-model simply means the integration of the model into an existing production environment which can take in an input and return an output that can be used in making practical business decisions. It is one of the last stages in the machine learning life cycle and can be one of the most cumbersome.
Top machine learning platforms we use
Amazon Web Services. Highly scalable, complete cloud platform. Microsoft Azure. IaaS and PaaS computing for development, deployment, and management. Google Cloud Platform. Developer products and cloud technologies hosted by Google.
Machine Learning on AWS
Building and Deploying AI and ML Models with Amazon SageMaker
Machine Learning on Azure
Developing Machine Learning Models with Azure Machine Learning Studio
Machine Learning on Google Cloud
Building Machine Learning Models on Google Cloud with Cloud Machine Learning Engine
Machine Learning Frameworks
Building Machine Learning Models with Open Source frameworks - TensorFlow, Theano and Keras