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Monday 9am - 7pm Tuesday 9am - 7pm Wednesday 9am - 7pm Thursday 9am - 7pm Friday 9am - 7pm

REDX WeSchool

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REDX WeSchool

P. Mandali’s Prin. L. N. Welingkar Institute of Management Development and Research (WeSchool).

REDX WeSchool develops technology-based, citizen-centric solutions to support growing needs of the next 5 billion; leveraging Artificial Intelligence, Data analytics, Imaging technologies, Design and Internet of Things. REDX (Rethinking Engineering Design eX*****on) is a unique, anti-disciplinary, bottom-up, co-innovation platform designed to solve the most pressing challenges within our communiti

es (http://redx.io/).

‘REDX-WeSchool’ is an Innovation Lab at S. It is a vibrant ecosystem of Innovation, rolling out new and innovative, citizen-based technologies that support wide-ranging needs of urban populations. The focus is to leverage:
- Imaging and digital technologies, ultra low-cost hardware, mobile platforms and Internet of Things,
- Design skills like Design Thinking, Design Research, Design ethnography, concept prototyping, Design validation, Localisation, Authentic design and Brand Storytelling
- Artificial Intelligence, Deep Learning, Machine Learning and Computer Vision to develop tech-enabled innovations

Our innovations have so far attempted to solve real-life challenges from multiple areas like medical/ healthcare industry, civic issues like urban development & waste management and financial inclusion.

23/06/2022

Wonderful session on Cyber Security conducted by Mr. Tamaghna Basu yesterday! ✨

Missed it? Watch it soon on our YouTube channel - REDX WeSchool!

17/06/2022

Here are 4 podcasts we recommend personally to help you learn something new today!

15/06/2022

The wait is over! 🤩
Mark your calendars for our next session on Innovations and Machine Learning Algorithms in Cyber Security with Mr. Tamaghna Basu, Co-Founder & CEO, DeTaSECURE.

Catch the event Live on Welingkar institute’s official YouTube channel!
(WeSchool students can join in live through Zoom and also get a chance to interact with our speaker!)✨

See you there!

12/06/2022

All that’s been happening in the Tech world! ✨

05/06/2022

This World Environment Day let’s pledge to build a better tomorrow! 🌏🌱

#2022

03/06/2022

Although, Stranger Things may seem all fiction but is it really?

Read about the Montauk’s Camp Hero and how it may actually have influenced the famous Netflix series! 😮

27/05/2022

A company has a data moat if its access to data makes it difficult for competitors to enter its business. Moat is a common business term used to evoke the water-filled moats built around castles to make them easier to defend against attackers. For example, if a self-driving car company can acquire far more data than its competitors to train and test its system, and if this data makes a material difference in the system’s performance, then its business will be more defensible.

🟠 A data moat may not do much to protect an AI business if:

● System performance plateaus with more data. Say you're building a general-purpose speech recognizer, and human-level performance is 95 percent accurate. Collecting enough data to achieve 94 percent accuracy is hard, and getting incrementally more

data will have diminishing returns. In fact, it’s much easier for a competitor to improve
from 90 to 91 percent accuracy than for you to improve from 94 to 95 percent.

● Data doesn’t change over time. If the mapping from input x to output y remains the
same (as in speech recognition, where the input spoken words “The Batch” will continue to map to their text equivalents for a long time), competitors will have time to accumulate data and catch up.

● The application can be built with a smaller dataset thanks to new data-centric AI development technologies, including the ability to generate synthetic data, and tools that systematically improve data quality.

🟢 Given these circumstances, data can make an AI business more defensible if:

● Performance keeps improving materially within the range of dataset size that a company and its competitors can reasonably amass.

● The data distribution varies significantly over time. In this case, access to an ongoing stream of fresh data is critical for keeping the machine learning model current, which in turn earns further access to the data stream.

● The market has winner-take-all dynamics, and users have low switching costs. When a market supports only one leader, access to data that delivers even marginally better performance can be a major advantage.

Now Hiring! 💡📄LEAD RESEARCH ENGINEERCome work with us. 🤩Interested candidates send in your CV and Cover letter at redx@w...

18/05/2022

Now Hiring! 💡📄
LEAD RESEARCH ENGINEER

Come work with us. 🤩

Interested candidates send in your CV and Cover letter at [email protected]

13/05/2022

What is Web 3.0? 🤔

Here’s what you need to know about it. 🔝

Let us know your thoughts in the comments below👇🏼

Follow for more such content! 🔥

06/05/2022

Transfer learning will be the next driver of machine learning’s commercial success after supervised learning. 💡

Using State-of-the-Art Pre-trained Neural Network Models we can tackle Computer Vision Problems with Transfer Learning.🧬

Here are a few pre-trained networks you can use for computer vision tasks such as ranging from image generation, neural style transfer, image classification, image captioning, anomaly detection, and so on. 🤩

Follow for more such content! 🔥

29/04/2022

All that you need to know about the latest news in Tech! 🔥

22/04/2022

Types of Neural Networks, its uses and advantages & disadvantages curated all in one place for you! 🫶🏽🤩

Source: geeksforgeeks.org
Levity.ai

Address

612A, Prin. L. N. Welingkar Institute Of Management Development And Research, L. N. Road, Matunga East
Mumbai
400019

Opening Hours

Monday	9am - 7pm
Tuesday	9am - 7pm
Wednesday	9am - 7pm
Thursday	9am - 7pm
Friday	9am - 7pm

Telephone

+91 24198300 (5045)

Website

http://redx.welingkar.org/

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