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Aishwarya Nambissan @AishLearnsAI
Joined July 2023
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  • Following 6
  • Followers 5
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Dimensionality reduction results in fewer input variables which allows for a simpler predictive model that may have better performance when making predictions on new data. #aigraph machinelearningmastery.com/l…

Linear Discriminant Analysis for Dimensionality Reduction in Python - MachineLearningMastery.com

Reducing the number of input variables for a predictive model is referred to as dimensionality reduction. Fewer input variables can result in a simpler predictive model that may have better perform...

machinelearningmastery.com
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Engineers can now test models without worrying about privacy concerns since generative AI can produce large amounts of synthetic data that mirrors real-world information #aigraph towardsdatascience.com/5-gen…
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LLMs cannot understand written text directly, so Sentence Embedding is carried out. Thanks to the large dimension of the vector created by embedding, small variations in the data can be seen with greater precision. #aigraph towardsdatascience.com/maste…
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Reinforcement learning with human feedback is a possible means of addressing harmful biases in language models. #aigraph doi.org/10.48550/arXiv.2102.…
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The Deep Feature-Based Text Clustering is based on a deep pretrained model that can construct the meaning of words by contextual information, avoiding the processing of high-dimensional sparse features. #aigraph ieeexplore.ieee.org/document…
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For easy pandas functions for plotting data by different approaches to expose interesting structures: machinelearningmastery.com/q… #aigraph

Quick and Dirty Data Analysis with Pandas - MachineLearningMastery.com

Before you can select and prepare your data for modeling, you need to understand what you've got to start with. If you're a using the Python stack for machine learning, a library that you can use to...

machinelearningmastery.com
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Hierarchical clustering has high space and time complexity. So, this clustering algorithm cannot be used for large datasets. #aigraph towardsdatascience.com/under…
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AI technology has the potential to improve workplace safety and efficiency by analyzing task completion patterns. Hyundai and Mercedes-Benz are using AI embedded in exoskeletons to help human workers to perform most repetitive tasks better. #aigraph doi.org/10.1016/j.jbusres.20…
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Labeling textual data without access to gold-standard labels is a challenge. Topic modelling with some human intuition for fine tuning overcomes this challenge to quite an extent. #aigraph medium.com/@power.up1163/uns…

Unsupervised Text Classification with Topic Models and Good Old Human Reasoning

Use your brain and your data interpretation skills, and create production-ready pipelines without labeled data

medium.com
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The memory requirements for Llama-2 does not make it a feasible option for researchers to use on their own systems. Petals is a potential alternative as it provides access to public servers that researchers can use for their LLMs. #aigraph pub.aimind.so/this-is-why-yo…

This Is Why You Can’t Use Llama-2

How One Open-Source Project Is Democratising Access to LLMs

pub.aimind.so
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Subject classification is done to help combine resources by subject, but it is done manually since it requires a lot of training. Automated subject classification techniques are now introduced: upstream.force11.org/attempt… #aigraph

Attempts at automating journal subject classification

We had the training data for journal-level subject classification; it was a good place to begin understanding what would be needed.

upstream.force11.org
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By providing appropriate prompts, ChatGPT can be used for data analysis and exploration, interpreting key insights, performing literature review and identifying research gaps . #aigraph machinelearningmastery.com/a…

Advanced Techniques for Research with ChatGPT - MachineLearningMastery.com

Research has always been essential to human progress and has evolved tremendously over the past few years. With the advent of advanced technologies, new tools and techniques have emerged to conduct...

machinelearningmastery.com
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Large Language Models can be leveraged to direct clustering algorithms during semi-supervised learning, thus requiring less input from the experts. #aigraph doi.org/10.48550/arXiv.2307.…

Large Language Models Enable Few-Shot Clustering

Unlike traditional unsupervised clustering, semi-supervised clustering allows users to provide meaningful structure to the data, which helps the clustering algorithm to match the user's intent....

arxiv.org
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CLUSTERLLM is a novel text clustering framework that takes feedback from an instruction-tuned large language model, such as ChatGPT to guide a small embedder for finding text clusters with low cost. #aigraph doi.org/10.48550/arXiv.2305.…

ClusterLLM: Large Language Models as a Guide for Text Clustering

We introduce ClusterLLM, a novel text clustering framework that leverages feedback from an instruction-tuned large language model, such as ChatGPT. Compared with traditional unsupervised methods...

arxiv.org
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Sentence transformers are LLMs that are specially trained to output embeddings at the sentence level rather than the word or token level. These sentence level embeddings do a better job of capturing meaning and are far quicker to compute. #aigraph medium.com/@swansburg.justin…

How to Use LLMs to Build Better Clustering Models

A quick guide on a new way to leverage large language models to improve the separation across your clusters

medium.com
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Linear models with a rank constraint and a fast loss approximation can train on a billion words within ten minutes, while achieving performance on par with the state-of-the-art for tag prediction and sentiment analysis. #aigraph doi.org/10.48550/arXiv.1607.…

Bag of Tricks for Efficient Text Classification

This paper explores a simple and efficient baseline for text classification. Our experiments show that our fast text classifier fastText is often on par with deep learning classifiers in terms of...

arxiv.org
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Instruction Tuning and Reinforcement Learning with Human Feedback are 2 training steps that were applied to ChatGPT to make it work so well. #aigraph mark-riedl.medium.com/a-very…

A Very Gentle Introduction to Large Language Models without the Hype

1. Introduction

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AIaaS constitutes a new and unexplored electronic market. They will provide new ways to learn from customer data and provide advice or instructions without being specifically programmed to do so. #aigraph doi.org/10.1007/s12525-021-0…

Machine learning and deep learning

Electronic Markets - Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from...

link.springer.com
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To improve the level of precision for text classification use TF-IDF method for feature extraction. #aigraph doi.org/10.1007/978-3-319-67…

Using Text Mining Techniques for Extracting Information from Research

Nowadays, research in text mining has become one of the widespread fields in analyzing natural language documents. The present study demonstrates a comprehensive overview about text mining and its...

link.springer.com
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When the label space for describing a text is unlimited, Zero shot learning is used which involves classifying instances into categories without any labelled training data. #aigraph doi.org/10.48550/arXiv.2308.…

Using Large Language Models to Automate Category and Trend...

Purpose: In this paper, we present an automated method for article classification, leveraging the power of Large Language Models (LLM). The primary focus is on the field of ophthalmology, but the...

arxiv.org
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