I am hiring a AI / ML research scientist / engineer to bring in state of the art advances in AI (DL, Graph, NLP etc) to the world of Fintech at PayPal...please DM me if interested! Job posting below - https://www.linkedin.com/posts/vidyut-naware-4a23697_aiml-datascience-activity-6666088095177408513-6r9Y
Linkedin
Vidyut Naware on LinkedIn: #aiml #datascience | 551 comments
I am hiring a AI / ML research scientist / engineer to bring in state of the art advances in AI (DL, Graph, NLP etc) to the world of Fintech at PayPal.... 551 comments on LinkedIn
Learn AI/NLP and Machine Learning needed and deploy your own AI based Intelligent Chatbot.
Also learn how to earn cash after learning to build your own chatbot.
Kickstart your chatbot journey with our 6 Days Workshop starting from 12th June.
Participants will also get an AI Chatbot Cheetsheet and all the recorded sessions in free from theMAD.
The revolution of bots taking shape!
Are you part of this revolution?
Enroll now in just Rs 16 per day.
🔗 Link for enroll is here...
https://allevents.in/online/80002220391294
Other details on the above link 👆
Also learn how to earn cash after learning to build your own chatbot.
Kickstart your chatbot journey with our 6 Days Workshop starting from 12th June.
Participants will also get an AI Chatbot Cheetsheet and all the recorded sessions in free from theMAD.
The revolution of bots taking shape!
Are you part of this revolution?
Enroll now in just Rs 16 per day.
🔗 Link for enroll is here...
https://allevents.in/online/80002220391294
Other details on the above link 👆
AllEvents.in
Build A.I. ChatBot In 6 Days Workshop | Batch 4
Find event details and tickets information for Build A.I. ChatBot In 6 Days Workshop | Batch 4 Hosted By the MAD. Event starts at Tue Oct 13 2020 at 06:00 pm and happening at Online.
CREME – python library for online ML
All the tools in the library can be updated with a single observation at a time, and can therefore be used to learn from streaming data.
The model learns from one observation at a time, and can therefore be updated on the fly. This allows to learn from massive datasets that don't fit in main memory. Online machine learning also integrates nicely in cases where new data is constantly arriving. It shines in many use cases, such as time series forecasting, spam filtering, recommender systems, CTR prediction, and IoT applications. If you're bored with retraining models and want to instead build dynamic models, then online machine learning might be what you're looking for.
Here are some benefits of using creme (and online machine learning in general):
• incremental – models can update themselves in real-time
• adaptive – models can adapt to concept drift
• production-ready – working with data streams makes it simple to replicate production scenarios during model development
• efficient – models don't have to be retrained and require little compute power, which lowers their carbon footprint
api reference: https://creme-ml.github.io/content/api.html
github: https://github.com/creme-ml/creme
All the tools in the library can be updated with a single observation at a time, and can therefore be used to learn from streaming data.
The model learns from one observation at a time, and can therefore be updated on the fly. This allows to learn from massive datasets that don't fit in main memory. Online machine learning also integrates nicely in cases where new data is constantly arriving. It shines in many use cases, such as time series forecasting, spam filtering, recommender systems, CTR prediction, and IoT applications. If you're bored with retraining models and want to instead build dynamic models, then online machine learning might be what you're looking for.
Here are some benefits of using creme (and online machine learning in general):
• incremental – models can update themselves in real-time
• adaptive – models can adapt to concept drift
• production-ready – working with data streams makes it simple to replicate production scenarios during model development
• efficient – models don't have to be retrained and require little compute power, which lowers their carbon footprint
api reference: https://creme-ml.github.io/content/api.html
github: https://github.com/creme-ml/creme
GitHub
GitHub - online-ml/river: 🌊 Online machine learning in Python
🌊 Online machine learning in Python. Contribute to online-ml/river development by creating an account on GitHub.
Last time the seats got booked very soon and many were not able to participate.
And Looking at what amazing things participants of Batch 1 have build and after having best reviews from them we are coming up with the Batch 2 for AI Chatbot Development workshop just for you.
Now don't miss.. else you will miss something extremely important and special in your life and career.
Limited seats!! 🔥 🔥
So Hurry before it gets full!
It's a race.
Enroll now 💥
http://www.wethemad.in/courses/chatbot_dev.php
Find other details of the workshop on this link.
And Looking at what amazing things participants of Batch 1 have build and after having best reviews from them we are coming up with the Batch 2 for AI Chatbot Development workshop just for you.
Now don't miss.. else you will miss something extremely important and special in your life and career.
Limited seats!! 🔥 🔥
So Hurry before it gets full!
It's a race.
Enroll now 💥
http://www.wethemad.in/courses/chatbot_dev.php
Find other details of the workshop on this link.
In just ₹ 25/day get the best learning experience that u can never imagine! 🔥
Practitioner’s Guide to Statistical Tests
CoreML team at VK
If you want to learn how to choose the right statistical test from the many available and run it on your own data you can find the answer at this article.
The two most essential things in A/B tests are the design of the experiments and accurate analysis of the experiments’ results. In this article, the authors stuck to the most common design and compare various statistical analysis procedures, from the very standard t-test and Mann-Whitney test to state-of-the-art approaches like the reweighted bootstrap.
article: https://medium.com/@vktech/practitioners-guide-to-statistical-tests-ed2d580ef04f
github: https://github.com/marnikitta/stattests
#statistic #ab #tests #vktech
CoreML team at VK
If you want to learn how to choose the right statistical test from the many available and run it on your own data you can find the answer at this article.
The two most essential things in A/B tests are the design of the experiments and accurate analysis of the experiments’ results. In this article, the authors stuck to the most common design and compare various statistical analysis procedures, from the very standard t-test and Mann-Whitney test to state-of-the-art approaches like the reweighted bootstrap.
article: https://medium.com/@vktech/practitioners-guide-to-statistical-tests-ed2d580ef04f
github: https://github.com/marnikitta/stattests
#statistic #ab #tests #vktech
Medium
Practitioner’s Guide to Statistical Tests
Hi, we are Nikita and Daniel from the CoreML team at VK. It’s our job to design and improve recommender systems for friends, music, videos…
Machine Learning
Practitioner’s Guide to Statistical Tests CoreML team at VK If you want to learn how to choose the right statistical test from the many available and run it on your own data you can find the answer at this article. The two most essential things in A/B…
Do read this article! It will add enough value to your statistical knowledge. 💯
Time for understanding ML and DL in Automobile Industry from a Data scientist at Mercedes-Benz.
An Introduction to the Powerful Bayes' Theorem for Data Science Professionals
https://www.analyticsvidhya.com/blog/2019/06/introduction-powerful-bayes-theorem-data-science/
https://www.analyticsvidhya.com/blog/2019/06/introduction-powerful-bayes-theorem-data-science/
Analytics Vidhya
An Introduction to the Powerful Bayes' Theorem for Data Science Professionals
Bayes theorem is a powerful concept of statistics every data science professional should know. Learn what is Bayes theorem and applications of Bayes theorem
Have you ever wondered Why Naive Bayes is called Naive?
Check this recent post out :
https://www.instagram.com/p/CDBaAdBAQWH/?igshid=18e79sd43y4p4
Like, share and comment if you found it valuable.
Machine Learning taught right ❤️
Check this recent post out :
https://www.instagram.com/p/CDBaAdBAQWH/?igshid=18e79sd43y4p4
Like, share and comment if you found it valuable.
Machine Learning taught right ❤️
Instagram
The MAD - Alpha
In statistics, Naïve Bayes classifiers are a family of simple "probabilistic classifiers" based on applying Bayes' theorem with strong independence assumptions between the features. But today let's see, Why they are called Naives. What's the secret behind…