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Sharmistha Chatterjee
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  • Bangalore
  • India
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Sharmistha Chatterjee liked ajit jaokar's blog post Feature engine python package for feature engineering
4 hours ago
Vidya Manu Shankar liked Sharmistha Chatterjee's blog post ARIMA/SARIMA vs LSTM with Ensemble learning Insights for Time Series Data
Jul 28
Kabilan Mohanraj liked Sharmistha Chatterjee's blog post ARIMA/SARIMA vs LSTM with Ensemble learning Insights for Time Series Data
Jul 28
Sharmistha Chatterjee posted blog posts
Jul 27
Sharmistha Chatterjee's blog post was featured

Blockdrop to Accelerate Neural Network training by IBM Research

Scaling AI with Dynamic Inference Paths in Neural NetworksIntroductionIBM Research, with the help of the University of Texas Austin and the University of Maryland, has tried to expedite the performance of neural networks by creating technology, called BlockDrop. Behind the design of this technology lies the objective and promise of speeding up convolutional neural network operations without any loss of fidelity, which can offer a great savings of cost to the ML community.This could “further…See More
Jul 26
Sharmistha Chatterjee posted blog posts
Jul 24
Sharmistha Chatterjee's blog post was featured

Traditional vs Deep Learning Algorithms in the Telecom Industry

Traditional vs Deep Learning Algorithms in the Telecom Industry — Cloud Architecture and Algorithm CategorizationGoogle Cloud Architecture for Machine Learning Algorithms in the Telecom IndustryIntroductionThe unprecedented growth of mobile devices, applications, and services have placed the utmost demand on mobile and wireless networking infrastructure. Rapid research and development of 5G systems have found ways to support mobile traffic volumes, real-time extraction of fine-grained…See More
Jul 23
Sharmistha Chatterjee shared their blog post on Twitter
Jul 19
Sharmistha Chatterjee's blog post was featured

Anomaly Detection from Head and Abdominal Fetal ECG — A Case study of IOT anomaly detection using Generative Adversarial Networks

Anomaly Detection from Head and Abdominal Fetal ECG — A Case study of IOT anomaly detection using Generative Adversarial NetworksUnsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal MetricsMotivationIn this blog, we discuss the role of Variation Auto Encoder in detecting…See More
Jul 19
Michael Y. Choi liked Sharmistha Chatterjee's blog post ARIMA/SARIMA vs LSTM with Ensemble learning Insights for Time Series Data
Jul 16
Sharmistha Chatterjee's blog post was featured

ARIMA/SARIMA vs LSTM with Ensemble learning Insights for Time Series Data

MotivationThere are five types of traditional time series models most commonly used in epidemic time series forecasting, which includesAutoregressive (AR),Moving Average (MA),Autoregressive Moving Average (ARMA),Autoregressive Integrated Moving Average (ARIMA), andSeasonal Autoregressive Integrated Moving Average (SARIMA) models.AR models express the current value of the time series linearly in terms of its previous values and the current residual, whereas MA models express the current value of…See More
Jul 16
Sharmistha Chatterjee shared their blog post on Twitter
Jul 15
Sharmistha Chatterjee shared their blog post on StumbleUpon
Jul 15
Sharmistha Chatterjee liked ajit jaokar's blog post 23 sources of data bias for #machinelearning and #deeplearning
Jul 13
Sharmistha Chatterjee's blog post was featured

Traditional vs Deep Learning Algorithms used in BlockChain in Retail Industry

Use of SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN in Retail with BlockChainIntroductionThis blog highlights different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail payments. This blog is structured as follows:Overview of the role of blockchain in the retail industry.Different traditional (SecureSVM, Bagging, BoostingClustering) vs deep learning algorithms (LSTM, CNN, and GAN) used in bitcoin retail payments.Blockchain in…See More
Jul 12
Sharmistha Chatterjee updated their profile
Jul 12

Profile Information

Company:
PublicisSapient
Job Title:
Senior Manager
Seniority:
Consultant
Job Function:
Data Scientist
Number of employees:
25.000 to 49.999
Industry:
Technology
LinkedIn Profile:
http://https://www.linkedin.com/in/sharmistha-chatterjee-7a186310/
Interests:
Contributing, Networking, New venture, Other

Sharmistha Chatterjee's Blog

Blockdrop to Accelerate Neural Network training by IBM Research

Posted on July 26, 2020 at 7:30am 0 Comments

Scaling AI with Dynamic Inference Paths in Neural Networks

Introduction

IBM Research, with the help of the University of Texas Austin and the University of Maryland, has tried to expedite the performance of neural networks by creating technology, called BlockDrop. Behind the design of this technology lies the objective and promise of speeding up convolutional neural network operations without…

Continue

Traditional vs Deep Learning Algorithms used in BlockChain in Retail Industry

Posted on July 26, 2020 at 7:22am 0 Comments

Use of SecureSVM, Boosting, Bagging, Clustering, LSTM, CNN, GAN in Retail with BlockChain

Introduction

This blog highlights different ML algorithms used in blockchain transactions with a special emphasis on bitcoins in retail payments. This blog is structured as follows:

  • Overview of the role of blockchain in the retail industry.
  • Different traditional…
Continue

Anomaly Detection from Head and Abdominal Fetal ECG — A Case study of IOT anomaly detection using Generative Adversarial Networks

Posted on July 26, 2020 at 7:14am 0 Comments

Anomaly Detection from Head and Abdominal Fetal ECG — A Case study of IOT anomaly detection using Generative Adversarial Networks

Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal…

Continue

ARIMA/SARIMA vs LSTM with Ensemble learning Insights for Time Series Data

Posted on July 26, 2020 at 7:09am 0 Comments

Motivation

There are five types of traditional time series models most commonly used in epidemic time series forecasting, which includes

  • Autoregressive (AR),
  • Moving Average (MA),
  • Autoregressive Moving Average (ARMA),
  • Autoregressive Integrated Moving Average (ARIMA), and
  • Seasonal Autoregressive Integrated Moving Average (SARIMA) models.

AR models express the current value of the time series linearly in…

Continue

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