This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
Data science platform market is estimated to rise with a CAGR of 31.1% by generating a revenue of $224.3 billion by 2026. Asia-Pacific holds the highest growth rate, expecting… Read More »Product Innovation Marketing Drives Global Data Science Platforms
Big data and data analytics have become a part of our everyday lives. From online shopping to entertainment to speech recognition programs like Siri, data… Read More »How Big Data Can Improve Your Golf Game
At my AI course in the University of Oxford, we are exploring the use of PyTorch for the first time. One of the best libraries… Read More »A simple way for getting started with fast.ai for pytorch
The Markov Decision Process (MDP) provides a mathematical framework for solving the RL problem. Almost all RL problems can be modeled as an MDP. MDPs… Read More »Markov Decision Processes
The number of devices connected through the Internet of Things (IoT) is increasing rapidly. Statista estimates that there will be about 50 million IoT-connected devices… Read More »Data Science and Cloud: A Perfect Match for your Data Analytics needs
This post continues our discussion on the Bayesian vs the frequentist approaches. Here, we consider implications for parametric and non-parametric models In the previous blog… Read More »The Bayesian vs frequentist approaches (Part 3) parametric vs non-parametric models
Judea Pearl (left) and Donald Rubin (right) taken in 2014. Full disclosure: I am a big fan of Judea Pearl and his contributions to Bayesian… Read More »Why I think the Potential Outcomes Theory is woefully incomplete without Pearl’s enhancements to it
We exist in a world where data is everywhere, not just data but an augmented data. Digging through this data is challenging but enforceable with… Read More »Why Augmented Data Analytics is the Future of Business Intelligence?
Source: here There are numerous examples in machine learning, statistics, mathematics and deep learning, requiring an algorithm to solve some complicated equations: for instance, maximum… Read More »An Easy Way to Solve Complex Optimization Problems in Machine Learning
Perhaps most organizations already know what to do with the data gathered. The data is used to make better decisions at work, right? But do… Read More »Top 6 Regression Techniques a Data Science Specialist Needs to Know
