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Data Science

Derive intelligent, accurate and data-driven decisions with Data Science

With the rise of AI and Automation, enterprises are redefining their IT strategy with a focus on exploiting data for competitive advantage. With the help of Data Science, businesses can understand phenomena via the automated analysis of data for better decision making, improved efficiencies, higher productivity, enhanced user engagement, and improved profitability. Innova’s data scientists and data professionals bring sophisticated data solutions that encapsulate complex services in accessible components that can significantly extend your company’s data capabilities and help enterprises take effective, intelligent, data-driven business decisions.

Our Approach

Our Service Offerings

Innova has deep expertise in data sciences and implemented advanced analytics projects, to several Fortune 500 customers across the globe. With our knowledge base over the years, we have fine-tuned our approach, methodology, solution accelerators, and processes to fit any data science engagement across any industry.

Leverage our supervised learning models to train algorithms to classify data and predict outcomes with accuracy. The algorithms that we offer include:

Linear Regression

Decision Tree

Random Forest

Logistic Regression

Our areas of expertise include:

Fraud Detection

Market Segmentation

Customer Segmentation

Pattern or Face Recognition

Image Classification

Marketing Forecasting

Advertising Popularity Predictions

Leverage our unsupervised learning models to analyze patterns and classify data with zero human intervention. The algorithms that we offer include

K-Means Clustering

Hierarchical Clustering

Gaussian mixture model

Our areas of expertise include:

Recommendation System

Customer Segmentation

Spam Filtering

News Classification

Social Network Analysis

Search Result Grouping

Image Segmentation

Anomaly Detection

Big Data Visualization

Feature Elicitation

Email Classification

Machine learning and artificial intelligence are now moving from the realm of research into adoption. This adoption driven by agile practices provides any organization with a competitive edge. On the other hand, MLOps incorporates the experimentation, iteration, and continuous improvement of the machine learning lifecycle. Its core benefits include – Efficiency – allowing data teams to achieve faster model development and deliver higher quality ML models; Scalability – where thousands of models can be controlled, managed, and monitored for continuous integration, delivery, and deployment; Risk reduction – enabling greater transparency and faster response to drift checks to ensure proper compliance with an organization’s policies.

Our Approach

With our unique ML implementation approach, organizations can:

Proactively address all common business concerns

Data-streaming dashboards

Enable consistent models by tracking data, code, and model versioning

Package and deliver models in repeatable configurations to maintain reusability

Predictive intelligence is a new machine learning-empowered solution that interconnects all data to predict outcomes and highlight all the key variables impacting organization performance. It gathers real-time data from various sources across the organization and helps anticipate market changes, missed assumptions, or future outcomes that are critical to making robust, business-wide decisions. Currently, the use of Predictive Intelligence is rapidly gaining momentum in many industries across the globe.

The growth of data astounds organizations across the globe today. Businesses are loaded with diversified data from many sources internally and externally, including devices, real-time sensors, mobile apps, and IoT. Yet, as unstructured data is exponentially growing, businesses are stuck with massive data and struggling to unlock valuable insights that could support their decisions and strategy.

Advertising Popularity Predictions

Leverage our supervised learning models to train algorithms to classify data and predict outcomes with accuracy. The algorithms that we offer include:

Linear Regression

Decision Tree

Random Forest

Logistic Regression

Our areas of expertise include:

Fraud Detection

Market Segmentation

Customer Segmentation

Pattern or Face Recognition

Image Classification

Marketing Forecasting

Advertising Popularity Predictions

Email Classification

Leverage our unsupervised learning models to analyze patterns and classify data with zero human intervention. The algorithms that we offer include

K-Means Clustering

Hierarchical Clustering

Gaussian mixture model

Our areas of expertise include:

Recommendation System

Customer Segmentation

Spam Filtering

News Classification

Social Network Analysis

Search Result Grouping

Image Segmentation

Anomaly Detection

Big Data Visualization

Feature Elicitation

Email Classification

AI/ML Engineering Ops

Machine learning and artificial intelligence are now moving from the realm of research into adoption. This adoption driven by agile practices provides any organization with a competitive edge. On the other hand, MLOps incorporates the experimentation, iteration, and continuous improvement of the machine learning lifecycle. Its core benefits include – Efficiency – allowing data teams to achieve faster model development and deliver higher quality ML models; Scalability – where thousands of models can be controlled, managed, and monitored for continuous integration, delivery, and deployment; Risk reduction – enabling greater transparency and faster response to drift checks to ensure proper compliance with an organization’s policies.

Our Approach

With our unique ML implementation approach, organizations can:

Proactively address all common business concerns

Data-streaming dashboards

Enable consistent models by tracking data, code, and model versioning

Package and deliver models in repeatable configurations to maintain reusability

Predictive Intelligence

Predictive intelligence is a new machine learning-empowered solution that interconnects all data to predict outcomes and highlight all the key variables impacting organization performance. It gathers real-time data from various sources across the organization and helps anticipate market changes, missed assumptions, or future outcomes that are critical to making robust, business-wide decisions. Currently, the use of Predictive Intelligence is rapidly gaining momentum in many industries across the globe.

iDSP

The growth of data astounds organizations across the globe today. Businesses are loaded with diversified data from many sources internally and externally, including devices, real-time sensors, mobile apps, and IoT. Yet, as unstructured data is exponentially growing, businesses are stuck with massive data and struggling to unlock valuable insights that could support their decisions and strategy.

Research

Data Science in Healthcare

White Paper

How Data Science Helps Providers in Improving Healthcare Outcomes

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