AI

Getting Familiar with Activation Function and Its Types.

Reading Time: 7 minutes Hey Folks, In this blog we are going to discuss activation function in Artificial Neural Networks and their different types. Before going there, let’s get some idea about what is an artificial neural network? Artificial Neural Network(i.e., ANN) Artificial Neural Network refers to a biologically inspired sub-field of Artificial Intelligence modeled after the brain. ANN is a computational network based on a biological neural network Continue Reading

Logistic Regression in Machine Learning: A Guided Tour

Reading Time: 4 minutes In this blog we will understand about the logistic regression and see its practical implementation on loan prediction. What is Logistic Regression? Logistic regression is a statistical and machine learning technique for classifying records of a data set based on the values of the input fields. Let’s say we have a loan data set that we’d like to analyse in order to understand which customers might be Continue Reading

Is SpaCy Python NLP Any Good? Seven Ways You Can Be Certain

Reading Time: 4 minutes SpaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python. If you’re operating with plenty of text, you’ll eventually want to know more about it. For example, what’s it about? What do the phrases suggest in context? Who is doing what to whom? Which texts are just like every other? Certainly, spaCy can resolve all the problems stated above. Linguistic Features in SpaCy SpaCy goes Continue Reading

Data Science Project Life Cycle

Reading Time: 2 minutes Overview The development life cycle of a data science project is different than the traditional software development life cycle. Though the development methodologies and practices vary across organisations but most of them have similar processes. One such well known process is the Cross Industry Standard Process for Data Mining (CRISP-DM) and this blog will present a summarised version of it. Data Science Life Cycle The life cycle of a data Continue Reading

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