Emerging and Disruptive Technology  

We are entering the digital era of “AI-powered by Deep Learning”. This disruptive technology promises innovative solutions, fresh markets, and unexpected ways to connect with customers and the market. The machinery is growing so the risk to society. DeepFake technology is emerging as a threat to the functioning of government, fundamentals of commerce, and social structure. The movie faceoff is slowly becoming a reality. Blending the human image on one-another is known as DeepFake. It is swapping out on the image of a one-person face with another person using disruptive technology, “Artificial Intelligence”. To demonstrate the potential destruction, the DeepFake technology can do, Jorden Peele creates this fake video of Ex-President Obama to show how easy it was to put words in someone else’s mouth. (More Read: Synthesizing Obama: Learning Lip Sync from Audio ) What is DeepFake? As per wiki ”DeepFake is a synthetic media in which a person in an existing image or vid

W orld Economic forum says about Deep Learning powered AI as “We stand on the brink of a technological revolution that will alter the way we live, work and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before”. What is Artificial Intelligence? Artificial Intelligence is a technology to simulate human intelligence in machines by making them think, solve problems and respond by learning like humans.  Once, Artificial Intelligence was science fiction because of the way the machines were trained with step-by-step instructions (billion lines of software code). Now it is a reality    –Thanks to changing in approach by teaching machines, called “Deep Learning”–A Technique for Implementing Machine Learning. Machine Learning, importantly Deep Learning technology, is driving Artificial Intelligence to the next level. What is Deep Learning? Before diving into Deep Learning, let us quic

The QuickDA is an open-source EDA tool that helps to build a successful data model from the structured dataset. Understanding the business model, getting reliable data, and preparing the data for modeling is another huge exercise. It is important to find out what each of the data points signifies. Most of the time the modeling is failed because of poor insight into data due to improper exploration & analysis. The finest data should be derived only by cleaning the available data before building the model. Data cleaning is an art. To create the finest art, you need the finest data. Otherwise, it is just a stained one. There’s an old saying, “garbage in, garbage out”; Most of the time understanding data demand lots of coding to make it perfect for modeling. The open-source EDA library, " QuickDA "  (a 𝘭𝘰𝘸-𝘤𝘰𝘥e python library for 𝘘𝘶𝘪𝘤𝘬 𝘌𝘹𝘱𝘭𝘰𝘳𝘢𝘵𝘰𝘳𝘺 𝘋𝘢𝘵𝘢 𝘈𝘯𝘢𝘭𝘺𝘴𝘪𝘴 of any structured data