AI

Personalization is paramount when targeting new customers in the banking industry

Reading Time: 5 minutes Established financial institutions need to target the right people at the right time. But truly seizing the opportunity in this space will require hyper-personalization. Most banking customers don’t think much about the industry unless they’ve reached a crossroads where they need a particular service. That means few people are actively looking to switch banks or are particularly susceptible to traditional marketing tactics. If banking customers Continue Reading

Machine-Learning-in-capital-market

Implementing Machine Learning in Capital Markets

Reading Time: 4 minutes When the COVID-19 outbreak became a global pandemic, financial-markets volatility hit its highest level in more than a decade, amid pervasive uncertainty over the long-term economic impact. Calm has returned to markets in recent months, but volatility continues to trend above its long-term average. Amid persistent uncertainty, financial institutions are seeking to develop more advanced quantitative capabilities to support faster and more accurate decision making. Continue Reading

Opinion: Is your Business Ready for AI on the Edge?

Reading Time: 4 minutes AI has traditionally been deployed in the cloud. AI algorithms crunch massive amounts of data and consume massive computing resources. But AI doesn’t only live in the cloud. In many situations, AI-based data crunching and decisions need to be made locally, on devices that are close to the edge of the network. At the Edge AI at the edge allows mission-critical and time-sensitive decisions to Continue Reading

AI: Making Agents Learn for Better Business Decisions

Reading Time: 3 minutes In our previous post we have talked about different types of agents that can be built for business. Any type of agent (model-based, goal-based, utility-based, etc.) can be built as a learning agent (or not). Learning allows the agent to know more than what it initially started with in terms of the operating environment. Components of a Learning Agent The learning agent can be divided Continue Reading

AI: Right Structure of Agents For your Business

Reading Time: 5 minutes In the previous post, we discussed the environment in which the agent operates and the characteristics of those environments. In this post let us talk about the types of agents and challenges of data set for the agents. All agents have the same skeletal structure. They get percepts as inputs from the sensors and the actions are performed through the actuators. Now the agent can Continue Reading

Thinking AI? Think Data First

Reading Time: 4 minutes There is a lot of interest in Machine Learning and AI. Ofcourse, a lot of it is still the level 1 of AI . This is when we are thinking about machines acting like humans. Everyone wants to jump on the bandwagon of AI. It is an amazing field and man organizations do not want to be left behind. That said, something which is ignored most of the time is the fuel, the data!

Product demand forecasting with Knime

Reading Time: 5 minutes In this blog, we are going to see, Importance of demand forecasting and how we can easily create these forecasting workflows with Knime. Market request forecasting is a basic procedure for any business, however maybe none more so than those in buyer packaged products. Stock, production, storage, delivering, showcasing – each aspect of CPG and retail organizations’ activities are influenced by accurate forecasting. Identifying shoppers’ Continue Reading

ROBOT PROCESS AUTOMATION

Reading Time: 2 minutes In today’s world that is continuously expanding and adopting new technologies every day, automation has also improved its ways in making our day to day work easier via ROBOT PROCESS AUTOMATION Sounds interesting ? You are wondering that automation has already helped us in many ways but now what’s this improved version of automation named as Robot Process Automation? So let’s dig into this and understand this buzz Continue Reading

MachineX: Run ML model prediction faster with Hummingbird

Reading Time: 3 minutes In this blog, we will see how to make our machine learning model’s prediction faster with a recently open-sourced library Hummingbird. Nowadays, we can see a lot of frameworks for deploying or serving the machine learning model into production. As a result, It is a headache for a data scientist to choose between these frameworks, keeping in mind how their model either Sklearn or LightGBM Continue Reading

COVID-19 Detector: Detecting Corona from X-Ray

Reading Time: 4 minutes A web application using deep learning to help medical practitioners to detect COVID-19 symptoms with chest x-rays. COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic by the WHO(World Health Organization) on 11 March 2020. The disease first originated in Wuhan, China and since then it has spread globally across the world affecting more than 200 countries. Coronavirus disease 2019 (COVID-19) Continue Reading

MachineX: Ultimate guide to NLP (Part 1)

Reading Time: 7 minutes In this blog, we are going to see some basic text operations with NLP, to solve different problems. This Blog is a part of a series Ultimate guide to NLP , which will focus on Basic text pre-processing techniques. Some of the major areas that we will be covering in this series of Blogs include the following: Text Pre-Processing Understanding of Text & Feature Engineering Continue Reading

MachineX: Boosting performance with XGBoost

Reading Time: 5 minutes In this blog, we are going to see how XGBoost works and some of the important features of XGBoost with the help of an example. So, many of us heard about tree models and boosting techniques. Let’s put these concepts together and talk about XGBoost, the most powerful machine learning Algorithm out there. XGboost called for eXtreme Gradient Boosted trees. The name XGBoost, though, actually Continue Reading