AI & Machine Learning

5 Ways To Digitize And Scale Your Retail Business With AI-Enabled Workflows

5 Ways To Digitize And Scale Your Retail Business With AI-Enabled Workflows Being the owner of a retail business has always been a tough job. It requires a lot of hard work and dedication. From the time you get up in the morning to the time you go to sleep at night, there are so

5 Distinctions Between Machine Learning And Deep Learning

What is Deep Learning, Anyway? As machine learning has gained significant notoriety for its wide-spread use across an immense number of applications, from retailers targeting products/marketing to individual consumers to high-frequency trading and quantitative models revolutionizing modern finance, and not to mention the seemingly constant media attention it gets in polemics surrounding privacy, user data,

10 MINUTES READ Continue Reading »

Duration Estimation In An A/B Test

While running an experiment, waiting for data is often the most challenging period as you are likely to get impatient. All you want during that period is for the A/B test to end as quickly as possible so you can go in a  full-scale execution mode. And, the anxiety adds up when you don’t know

5 MINUTES READ Continue Reading »
  • Top articles, research, podcasts, webinars and more delivered to you monthly.

  • Using Responsible AI To Teach The Golden Rule

    Business leaders have a delicate balancing act when it comes to AI. On one hand, according to O’Reilly, 85% of executives across 25 industries are tasked with either evaluating or deploying AI. On the other hand, risks and unintended consequences continue to grow, from Google search results showing offensively skewed results for “black girls”, to

    5 MINUTES READ Continue Reading »

    How Online Education In Data Science Helps Students To Become Work-Ready Graduates

    Data science is a relatively new field, but it has become central in all spheres of human activity. So, why the ongoing buzz around data science?  According to reports from IDC, the global ‘datasphere’ will expand to 175 Zettabytes by 2025. Now, that’s a lot of data. But, to get the best out of the

    4 MINUTES READ Continue Reading »

    Frequentist vs Bayesian Statistics: Which One Is Best!

    While performing statistical analysis, oftentimes, we face the dilemma about Frequentist Vs  Bayesian Strategy for the problem. This choice becomes critical when working with limited-sized datasets. And, if you use one method over the other without having a fundamental understanding of the assumptions and limitations of the two approaches, then you could increase your chance

    7 MINUTES READ Continue Reading »

    Principles To Ace In Your Job As A Data Scientist

    With the increasing amount of data generated and the evolution in the field of analytics, Data Science has turned out to be a necessity for companies to stay in the game. This has led to an increase in the demand for data scientists in various organizations to make sense of their vast amount of data.

    9 MINUTES READ Continue Reading »

    Ed Tech Apps – What You Can Expect By 2025

    Disruptive technologies have already begun to change the face of the education industry. The inclusion of emerging tech trends in the Edtech mobile application development process brings forth new and exciting learning opportunities for students and working professionals.

    5 MINUTES READ Continue Reading »

    6 Signs It’s Time To Automate

    Knowing when and where to invest in automation is key to making the most of it. In that spirit, here are six signs that it’s time to automate one or more of your processes.

    3 MINUTES READ Continue Reading »

    Time To Put An End To BERTology (Or, ML/DL Is Not Even Relevant To NLU)

    There are 3 technical reasons why the data driven / quantitative/statistical/machine learning approaches that are utterly hopeless and futile efforts, at least when it comes to language understanding.

    10 MINUTES READ Continue Reading »

    Learning Is Overrated: Machine Learning vs. Knowledge Acquisition

    Machine learning is important at the data-level — where we use our sensory inputs to recognize patterns and cognize of first-level objects— but what we know is a lot more and most of what matters is knowledge that is NOT learned but is knowledge that is acquired either by discovery or deduction or by being told.

    4 MINUTES READ Continue Reading »

    Getting Started With Reinforcement Learning

    Demystifying some of the main concepts and terminologies associated with Reinforcement Learning and their association with other fields of AI

    4 MINUTES READ Continue Reading »