Deep learning tools and ML algorithms help the business to gain tremendous popularity and profitability. Factors such as accurate analysis, cheaper and faster computational processing, and quick prediction have led to a massive boom in the business. Organizations can get quick benefit by using advancements in technologies and latest algorithms. At Umaginesoft, we assist in extracting meaningful information from a huge set of raw data, serve as a solution to a variety of business complexities problems and predict complex customer behaviors. Our machine learning expertise assist in business to enhance:
- Customer Value Prediction : Customer value prediction and segmentation are some of the major challenges faced by marketers today. Companies have access to a huge amount of data, which can be effectively used to build intelligent systems. Using this data, our team helps businesses to predict customer behaviors, purchasing patterns, and assists in sending the best possible offers to individual customers based on their browsing and purchase histories and other demographic information.
- Predictive Maintenance : Manufacturing firms regularly follow preventive and corrective maintenance practices, which are often expensive and inefficient. However, our ML specialists help to discover insights and patterns hidden in their factory data using deep learning and ML techniques. It helps in reducing the risks associated with unexpected failures and also eliminates unnecessary expenses. Our team members construct the architecture of difficulties of the company which can be built using historical data, workflow visualization tool, flexible analysis environment and feedback loop.
- Multi-class Email Classification : Generally, there are only two main category spam and ham. Our algorithm classifies ham mail in multiple categories, the main feature of our system is that it classifies ham mails in their respective classes.
- Product Recommendations : Product recommendation system is a collection of algorithms that designed to generate and provide suggestions for items or content, which user would like to purchase or get engaged with. Machine Learning algorithms are used for making product recommendations. ML and DL use customers purchase history, large product inventory to identify hidden patterns and group similar products. The system creates an advanced net of complex connections between the products and the customers and can suggest and motivate the customers for product purchase.
- Financial Analysis : T Machine learning has been extensively adopted in finance by traders for making market predictions. Due to the high volume of historical financial data generated in the industry, creates a challenge for the robust and precise prediction. Technology has come to play an integral role in many phases of the financial ecosystem, from approving loans for people to carrying out credit scores, fraud detection, portfolio management, algorithmic trading and assessing risk. The model is being used for analyzing historical market behavior, determining optimal inputs and strategies.
- Image Recognition & Analysis : Image recognition can produce numeric, symbolic information and other high-dimensional data from images. It involves data mining, ML, pattern recognition, and database knowledge discovery. Identifying fake images and modifications in the images e.g. forgery and cloning on the images is a big challenge. We use multiple algorithms to prove the images and find truthfulness. we also work on face recognition, facial feature and gesture detection.
- Medical Diagnosis : Using superior diagnostic tools and effective treatment plans, ML in medical diagnosis has helped several healthcare organizations to improve the patient's health and reduce healthcare costs. Smart machine learning algorithms are already used across different industries to replace repetitive, costly, and time-consuming tasks. The advantage of these algorithms and tools is that, unlike the human eye (and brain), they can capture unforeseen patterns within complex data sets at lightning speed. Predictions and insights are drawn using patient records and data sets along with the symptoms exhibited by the patient.
- Cyber Security & Surveillance : ML is being used for security & surveillance for industrial and user applications. Typical use cases are: 1. Detect weapons in videos. 2. Find and recognize person in videos. 3. Check abnormal activities in CCTV footage etc.
