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DS/ ML/ Analytics

Data Science Expertise & Methodology

Productionizing

Schedule model runs to provide predictions at selected intervals.

Monitor and tune models.

Business Understanding

Brainstorm with business users to identify potential use cases for data analytics.

Data Analytics

Choose appropriate machine learning technique (Predictive Modeling, Forecasting, etc.) Train relevant models.

Data Mining

Identify data sources and pull relevant data to build analytics data-marts.

Feature Engineering

Construct more meaningful features out of raw data.

Data Cleaning

Address the inconsistencies in the data.

Data Visualization

Create data visualizations to better understand relationship between variables of interest.

Data Exploration

Deep dive into the data to understand what insights can be generated.

Services

Provide your data and receive the results

Result-As-A-Service

Provide your data and receive the results
Develop and implement solutions

Analytics Advisory

Develop and implement solutions
Identify business problems to be solved

Analytics Workshops

Identify business problems to be solved
Dedicated services and support hosted at our location

Managed Services

Dedicated services and support hosted at our location
Third party products and solutions validation

Analytics Testing

Third party products and solutions validation

Machine Learning

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Infinity Quest offers a wide range of machine learning services to transform your business and build customized solutions running on an advanced machine learning algorithm. Our professionals help to provide solutions for businesses using the latest tools and technologies.

In this method, the input and output as well as feedback during training will be provided to the system. It also analyzes the accuracy of the system’s prediction during the training process. The main purpose of training is to make the system learn how to map an input to output.

Supervised Learning

In this method, the input and output as well as feedback during training will be provided to the system. It also analyzes the accuracy of the system’s prediction during the training process. The main purpose of training is to make the system learn how to map an input to output.
In this case, no such training is provided, and the system is allowed to find the output on its own. Unsupervised learning is mainly applied to transaction data. It is used for more complex tasks. It uses another iterative method called deep learning to draw some conclusions.

Unsupervised Learning

In this case, no such training is provided, and the system is allowed to find the output on its own. Unsupervised learning is mainly applied to transaction data. It is used for more complex tasks. It uses another iterative method called deep learning to draw some conclusions.
Reinforcement learning is different from the other types of supervised learning because the system doesn’t need any labeled input-output pairs. Alternatively, the system finds the best possible policy through trial and error.

Reinforcement Learning

Reinforcement learning is different from the other types of supervised learning because the system doesn’t need any labeled input-output pairs. Alternatively, the system finds the best possible policy through trial and error.

Our Offerings

Manufacturing Analytics

Manufacturing Analytics

Product Quality Analytics
Forecasting/ Demand Sensing
Supply-Chain Analytics
Inventory Optimization
Warranty Analysis
Utilities & Energy Analytics

Utilities & Energy Analytics

Customer Analytics
Outage Prediction
Smart Meter Analytics
Operation Analytics
Asset Management Analytics
Retail Analytics

Retail Analytics

Loyalty Analytics
Forecasting/ Demand Sensing
Personalized Offerings
Portfolio Management
Price & Promotion Analytics
Store Analytics
Healthcare Analytics

Healthcare Analytics

Patient Engagement & Satisfaction
Managing Customer Data
Medical Image Analytics
Resource Optimization
BFSI Analytics

BFSI Analytics

Customer Analytics
Personalized Offerings
Operation Analytics
DS/ ML/ Analytics

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