Machine Learning Development

In the last decade, the consulting industry has seen stimulating changes in machine learning, which have elevated its proficiencies across a set of applications. Growing data accessibility has permitted machine learning systems to be proficient on a large volume of data while raising data processing power supporting the analytical capabilities of these systems. These systems can thus carry out multifaceted progressions by learning from data, rather than following pre-programmed rules. As a result of these advanced analytical systems and the industry experts, Chromatus has performed specific tracking studies and consumer insights from machine learning techniques.

It has been observed that the machine learning applications can accomplish well at precise tasks. In most of the use cases, it was used to enhance human roles. Chromatus has closely followed and tracked industry verticals both at B2B and B2C level across industries with statistics and data science. This has provided a range of data model tools and data processing to analyse data. The machine learning field has helped in identifying the opportunities and challenges associated with the current market scenarios. Chromatus has identified and supported marketers in an underlying technology for both AI and data science. Thus, our statistical modelling approaches will inform how machine learning systems engage with likelihoods or uncertainty in strategic decision-making. This not only helps in creating algorithms that can learn from data but also make accurate predictions or decisions making. In years to come, Machine Learning techniques could be a key tool for market researchers, consultants, strategists and decision-makers to identify and analyse large datasets, catching the previously unanticipated patterns or extracting unexpected insights. Chromatus Consulting thus with the machine learning tools, has provided insights into the future with the help of past and present data. It completely negates the guesswork and guides your organization, customers, or the whole segments will change in the future.

Our approach to Machine learning is as follows  :

Analyze your strategic business needs and concept & product requirements

• Data Collection, Mining and Processing Data
• Feature Engineering
• Data Model Development
• Predictive analytics based on historical data
• Deploying a Prototype, Benchmarking
• Review and update the model