Machine Learning
- Deep learning
- Predictive analytics
- Statistical Modeling
- Supervised & Unsupervised Learning
Machine Learning is a set of techniques that gives web and mobile applications the ability to discover, accustom, and mature over time. It processes vast amounts of data, identifying trends and patterns, and learning from it. You can personalize your customer experience, automate processes, and implement solutions that will change the way customers interact with your product/services.
Our Experience with Machine learning
Deep learning
Deep learning is a subset of machine learning. It’s technically similar to machine learning and functions in many ways, but its capabilities are different. Basic machine learning models do become progressively better at whatever their purpose is, but they still need some guidance. But with a deep learning model, the algorithms can determine on their own if a forecast is accurate or not. Our experts create algorithms in neural networks that help to maintain accuracy in problems like image recognition, sound recognition, recommender system, and NLP. Our custom-built deep learning solutions help you build robust and intelligent AI network models that are capable enough to learn complex representations of data automatically. Our developers focus on providing deep learning implementation services to solve your business challenges.
Predictive analytics
The shift to digital is well underway. Operating in real-time is now a fundamental requirement rather than a nice-to-have. Organizations can use in-house data on customer preferences to improve their offerings and study the data collected from different channels to achieve your goals. Our expertise in providing comprehensive big-data, business intelligence, and analytics solutions to global organizations help us create solutions that ensure data-driven growth. Our experts not only help implement predictive analysis but also help create a structured data pipeline that can observe threats, strengths, and opportunities. Our predictive models use variable selection algorithms, best-practice and cross-validation methods to break through the noise in big data, pinpoint essential variables, and deliver accurate predictions of market outcomes based on validation data.
Statistical Modeling
With us, you can leverage the opportunity to achieve a top-notch modeling service based on reasoning and relevant statistical models. This analysis further helps you make suitable decisions for improvement in the functions of the company. Our experts apply various statistical models to the data they are investigating and are capable of understanding and interpreting the information visually. Rather than sifting through the raw data, this practice allows them to identify relationships between variables, make predictions about future sets of data, and visualize that data so that non-analysts and stakeholders can consume and leverage it. We have over a decade of domain expertise in retail, healthcare, media & entertainment, FMCG and eCommerce, with a focus on generating ROI.
Supervised & Unsupervised Learning
In machine learning, there are two essential categories- Supervised and Unsupervised. Our experts use supervised learning techniques on a fully labeled/classified data set to train the algorithm. We apply the information gathered in the past to new data using labeled examples to predict the answers. Once the system is trained with a data set, the learning algorithm can produce an inferred function that can compare its outcomes with the desired outputs provided in the training data set and adapt the model to be more accurate. In Unsupervised machine learning, our experts use data that is not classified, categorized, or labeled. Although it does not aim to produce specific outputs, the algorithm can analyze and detect similarities within the data set as well as make predictions.
