Machine Learning

Machine Learning Practice

Cloudwick on Amazon Web Services (AWS) seeks to bridge the gap between the developers that build machine learning models and business users. Integrated with Amazon SageMaker, Cloudwick enables users to rapidly deploy different machine learning models into a production system with minimal effort. This allows users to make copies of machine learning notebooks, edit notebooks, and deploy new versions of machine learning models and take advantage of deep analytics, supported by rich visualizations.

  • Assessment

    Engage in ML use case discussions with the customer and discover the ideal artificial intelligence, data lake, and machine learning approach that best fits the need of the organization.

  • Define KPI’s

    Obtain detailed insights reports, ongoing support, and personalized help from Cloudwick’s team of experts.

  • Data Lake

    Provide the skillset needed for data science, data engineering and extract, transform, load (ETL), along with setting up an AWS environment if needed.

  • Build and Productionalize

    Feature engineer, train, test and validate the ML model. Integrate with the application

  • Maintaince

    Continually maintain the ML models to assure business requirements are being fulfilled


Cloudwick provides the tools and expertise necessary for organizations to gain deep insights from their data through comprehensive machine learning models, without the need for developer intervention.

  • Variety of Supported Use Cases

    Enable users to leverage the Cloudwick platform for a multitude of use cases

  • Support for your customers

    Jumpstart the machine learning journey for your customers by providing an easy to navigate platform

  • Comprehensive visualizations

    Realize immediate business value with descriptive visualizations of inferred results

  • Simplified Data Exploration

    Bring machine learning into the hands of all users, allowing them to explore and understand data from a single platform


From accurate sales forecasting for retail environments, to financial institutions predicting the likelihood of credit defaults for new customers, Cloudwick’s machine learning capabilities can meet the analytics needs of organizations across numerous verticals. By automating the entire machine learning workflow, both business users and developers can spend more time leveraging forecast models to drive results and make more informed business decisions, and less time extracting and processing data

Note: Users are responsible for AWS infrastructure cost if you choose to deploy the below solutions on to your AWS account. 


Sales Forecast Prediction

Sales forecasting is an important tool for any growing business especially to determine future revenue and planning for any demand and will help make many important business decisions.

Accurate sales forecasting can help you track data to gain insight into areas where improvements can be made.

Such predictions can have huge impact on development of business. Our goal is to accurately predict weekly sales figures for a given a store and department among a total of 45 stores and 99 departments.

Please click the below links for a live demo or to deploy the solution to your AWS account.


Flight Delay Prediction

Flight delays hurt airlines, airports, and passengers. Their prediction is crucial during the decision-making process for all players of commercial aviation. Moreover, the development of accurate prediction models for flight delays became cumbersome due to the complexity of air transportation system, the number of methods for prediction, and the deluge of flight data. Our objective is to use machine learning techniques to predict flight delays at take off by considering factors affect the flight delays and leveraging big data to streamline the travel experience.

Please click the below links for a live demo or to deploy the solution to your AWS account.


Credit Default prediction

Americans owed over $1.03 trillion in credit-card debt as of April’18. Having existing customers or acquiring new ones who are likely to default on their payments is bad for business. The ability to identify these customers beforehand can help lending institutions in making proactive decisions to avoid such situations and plan their own finances accordingly. In this use case, we will use past 6 months of data points such as bill amount, amount paid, delay in payment and demographic factors such as age, gender and education level to predict whether a customer will default on their next payment or not.

Please click the below links for a live demo or to deploy the solution to your AWS account.

Public Sector

Traffic Prediction 

This analysis is to predict the traffic in a location at a given time, i.e., given a time and date, what would be the predicted traffic at that location (Junction). The insights from this analysis would help any organization/government to understand the traffic pattern of the city over the day. This has the potential to be one of the key models to help smart city initiatives.

Few of the fundamental applications of this predictive analysis would be:

  • To help the government in the implementation of a robust traffic system for the city by being prepared for traffic peaks, understand the traffic patterns at various junctions in the city.
  • To provide data-driven insights for future infrastructure planning for cities.

Please click the below links for a live demo or to deploy the solution to your AWS account.

Health Care

Dementia Onset Prediction

Dementia is a general term for a decline in mental ability severe enough to interfere with daily life. Memory loss is an example. We propose to develop a sound model that can help clinicians predict early Alzheimer’s for proactive identification. Considering that we have to predict whether a patient might have dementia or not, this is a binary classification problem.

Medical Appointment Show Up

Patients that do not show up for their appointment without advanced warning is an issue that negatively affects medical centers across the US because each no-show lowers access and is a missed billing opportunity. This is a substantial problem because average no-show rates are ~30% nationwide and account for $150 billion in wasted costs. This project is an attempt to lower the number of patients that no-show by  using Machine learning

Please click the below links for a live demo or to deploy the solution to your AWS account.


Churn Prediction

Customer churn refers to the situation when a customer ends their relationship with a company, and it’s a costly problem.

Customers are the fuel that powers a business. Loss of customers impacts sales. Further, it’s much more difficult and costly to gain new customers than it is to retain existing customers.

As a result, organizations need to focus on reducing customer churn. The good news is that machine learning can help.

For many businesses that offer subscription based services, it’s critical to both predict customer churn and explain what features relate to customer churn.

Our objective is to use machine learning techniques to predict the percentage of churn in an organization using big data and machine learning

Please click the below links for a live demo or to deploy the solution to your AWS account.

About Us

Cloudwick is the leading provider of enterprise business and technology modernization services and solutions to the Global 1000. We help leading enterprises  gain competitive advantage from open source, data lake, big data, cloud and advanced analytics.

  • Solutions

    Cloudwick provides complete data, analytics and cloud modernization solutions, leading to faster time-to-transformation for your enterprise.

  • Services

    Cloudwick makes business and IT transformation easy for line of business and IT with end-to-end data analytic and cloud modernization services.

  • Competencies

    Cloudwick has unmatched expertise and extensive experience architecting, scaling and managing enterprise data lake, advanced analytics, cloud and big data solutions.

  • Verticals

    Cloudwick has global experience and expertise working with executives, line of business, IT and vendors across all verticals.