Behind the Scenes: AI’s Technological Advances in the Entertainment Industry
Discover how Generative AI revolutionises filmmaking, enhancing creativity, reducing costs, and driving innovation.
Leveraging AI for Sustainable Business Operations: A Data-Driven Approach to Climate Change Mitigation
Leveraging AI for sustainable business operations has never been more critical than in the wake of the present climate change challenges. Recent events underscore the urgency of adopting a data-driven approach to climate change mitigation. The catastrophic wildfires in Canada, causing hazardous air quality in parts of the United States including Philadelphia and New Jersey, …
Explainable AI (XAI): Unlatching black box
Growing Need for Clarity in AI Systems In today’s rapidly evolving landscape, AI algorithms and machine learning systems have permeated numerous sectors. Data-driven problem-solving strategies are now commonplace, with significant advancements in applied machine learning systems becoming increasingly evident, particularly in the field of deep learning. However, the complexity of these systems has given rise …
Cracking the Data Scientist Role in Top Notch Tech Companies: A Guide for Aspiring Data Scientists
Data Science has become one of the most sought-after careers in today’s job market, particularly in top notch tech companies like Amazon, Meta (Facebook), Google, and Netflix. However, the skills and qualifications required for a data scientist role can vary greatly between companies. In this blog post, we’ve analyzed over 400 data scientist role-specific questions …
Synthetic Data Generation: A Guide for Machine Learning
Synthetic data generation is the process of creating artificial data that is designed to mimic real-world data. It is often used in machine learning and data science applications to augment or supplement existing datasets, or to generate data for testing and validation purposes. Why is Synthetic Data Generation Needed? There are several reasons why synthetic …
Attaining high confidence level through Model Calibration
There are many techniques to improve the performance of an AI model, out of these model calibration is one of the most efficient ways to attain high confidence in machine learning models by improving both model accuracy and fairness.Model calibration is a post processing technique to improvise probability estimates of an AI model. The objective …
Before building an AI startup
Global spending on Artificial Intelligence (AI) startups has been on continuous rise, from $4.25 billion in 2014, it reached $38 billion in 2021. This is an increase of 79% in a span of just 7 years. All major tech companies from Apple to Microsoft, from Google to Amazon, from IBM to Tesla have dedicated resources …