My Podcast on Data science & Machine Learning Learn Data Convergence Micro Podcast: Digital Transformation, Industry 4.0, IIoT & Emerging Tech CLICK HERE TO LISTEN
Read moreDr Venugopala Rao Manneni
Learner, Practitioner & Teacher
Digital Transformation, Industry 4.0, IIoT & Emerging Tech
Predicting the student Grade using PyCaret Auto ML Pipeline
PyCaret ( (https://pycaret.org/) is an open-source machine learning library that automates the entire process of training a machine learning model. When using it, you just need to have an idea of the best features you need to train your machine learning
Read more3 Key important qualities ever EHR Should Have
Due to the evolution of digital technology, data and algorithms, the healthcare sector transformed a lot and most of the hospitals are using the latest digital technologies such as Telehealth and EHR systems (Digital Electronic healthcare records). Electronic health record
Read moreLearning by applying and teaching a cyclic approach (Learn. Apply. Teach)
With the Motivation from Late M2 ( MRUTYUNJAY MISHRA) that by teaching we can learn more and every data person should Teach with this I started teaching/interacting with Academics from 2016 onwards through Key notes/ Guest lecturers/Faculty Developments and
Read moreHospital 2.0
Like all other industries, Healthcare industry is also disrupting with the digital revolution as well as with the speed of the processing, computing, network connectivity and algorithmic ability to handle the image and text data to provide the insights. With
Read moreData Scientist – The Generalized Specialist
As data science is more than Art it is science and more than science it is Art, due to this it requires some of the qualities beyond academic and programing skills which is Be Generalist and then Specialist Firstly who
Read moreAnalytics – Roundup 2020- Vision 2021
What is Left to New age data scientist is …
Presently we are in the era of automated machine learning (Auto ML), which helps automating most of the machine learning pipeline components such as data understanding, data engineering, feature engineering, model training, hyperparameter tuning, model monitoring, etc. and also there
Read moreWhy we need a mentor in Data science
As data science is everywhere due to the evolution of tools, computation power, speed, connectivity, storage systems and algorithms there is no way of getting out of working with it. Due to the pandemic the digitalization accelerated furthermore and changed
Read moreWHY AI is SOCIAL GOOD Technology
I believe that ‘technology/ AI’ does not have intrinsic value; its value lies in its application. I always say that I may create the best of algorithms with a great accuracy but it is only as useful as the problem
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