Too many cooks make the broth tastier.
Incorrect is the old adage: Too many cooks spoil the broth.
Updated adage in this age of AI and ML: Too many models make the accuracy higher.
Ensemble Learning in Machine Learning is when more than one machine learning algorithms merge to produce a better and more robust decision model, even though individually, they may be weak or average in predictions.… Continue reading
- According to a recent report on Indian Fintech ecosystem, India has achieved the second spot globally with largest number of Fintech Startups after US. Among all Fintech Startups, the ones who had maximum share were payment companies, lending, insurance and personal finance management Startups.
Sentiment Analysis using Doc2PC
Sentiment Analysis is the process of classifying the News/Text document as negative, slightly negative, neutral, slightly positive and positive. Sentiment analysis is based on advanced Natural language processing and Machine Learning Algorithms. It can also be used to classify type of news like Market, Financial or General News.… Continue reading
At its annual strategic review, NASSCOM announced that India’s IT-BPM industry grew 9.2 percent in 2018-19, during which it created 170,000 new jobs across large and mid-sized enterprises. Most of the job creations happened in the field of emerging technologies such as Artificial Intelligence (AI), data analytics, and cybersecurity, as companies across the spectrum ramped up their investments in digital transformation and innovation.… Continue reading
Sentiment Analysis (SA) in business, also known as opinion mining (OM) is a process of identifying and cataloging a piece of text according to the tone conveyed by it. The text can be tweets, comments, feedback, news or random texts with positive, negative and neutral sentiments associated with them…
G-Square’s Fund Ranking Model
An investor seeking capital gain for lower risk will always turn towards Mutual Fund schemes as an investment option, reason being its diversification and professional management.… Continue reading
- The total investment made by venture capital investors in the Indian startups stood at $7.9 billion in 2018, the third highest tally of the decade. A report released by global audit firm KPMG said that the deal sizes in India grew considerably last year, a sign of increasing maturation of the India VC market.
Latest Happenings in Data Analytics, AI and Fintech world
- Lok Sabha election 2019 is likely to focus a lot on data & data analytics. BJP did lot of with its hi-tech election campaign in the general elections of 2014. Similarly, other parties too have understood the significance of data-driven elections in making major influences on the results and have started diversifying their outlook away from the traditional ways of electioneering.
Text analytics through Summariser
Introduction of Text summary:
Text summarization is the process of identifying the most important meaningful information in a text document and compressing them into a shorter version preserving its overall meanings. Text Summarization is based on advanced Natural language processing and Machine Learning Technologies.… Continue reading
USE CASE IN CREDIT RISK ANALYTICS
The appetite for credit in a developing country like India is quite immense. The growing need of the large consumer Indian population and the Small & Medium Enterprises business segments (SME) for growing business to the next level is being tapped by the Indian financial institutions space.… Continue reading
- Prime Minister Modi was the keynote speaker at the Singapore Fintech festival, the biggest event of its kind in the world — attended by both industry leaders and smaller start-ups. He mentioned that India is witnessing an explosion of financial technology (Fintech) innovation and enterprise, Prime Minister Narendra Modi told the world’s largest gathering of Fintech firms in Singapore on Wednesday.
One of the interesting aspect of NLP on text mining is Topic Modelling.
Topic modeling is automatically discovering the abstract “topics” that occur in a collection of documents. Quite recently, topic models are being widely used to identify topics in a text corpus.… Continue reading