The rapidly evolving field of Large Language Models (LLMs) has seen a surge of new research recently. With the AI community constantly exploring new possibilities, it can be challenging to stay updated on the latest developments. In this post, I’m sharing my key takeaways from a deep dive into recent LLM research, highlighting some of … More A survey of recent LLM Research Papers
I recently attended the International Conference on Machine Learning (ICML), which showcased the latest research in machine learning, along with several valuable talks and sessions. In this post, I’ll outline the key insights and takeaways from the conference across various topics. Computer Vision 1) Scaling Vision Transformers to 22 Billion Parameters (paper) Researchers have made significant … More Learnings from ICML 2023
Last month, I had an opportunity to attend the KDD Conference in Washington DC. In this post, I’m sharing a summary of my learnings from the talks that I attended and/or found interesting. 1. Multimodal Learning Using Transformers to classify Multimodal Data This tutorial focused on using Transformers to classify multimodal data consisting of both … More Learnings from KDD 2022
What are Convolutional Neural Networks and why are they important? Convolutional Neural Networks (ConvNets or CNNs) are a category of Neural Networks that have proven very effective in areas such as image recognition and classification. ConvNets have been successful in identifying faces, objects and traffic signs apart from powering vision in robots and self driving cars. Figure 1: … More An Intuitive Explanation of Convolutional Neural Networks
An Artificial Neural Network (ANN) is a computational model that is inspired by the way biological neural networks in the human brain process information. Artificial Neural Networks have generated a lot of excitement in Machine Learning research and industry, thanks to many breakthrough results in speech recognition, computer vision and text processing. In this blog post we will try to … More A Quick Introduction to Neural Networks
This R package contains several tools to perform initial exploratory analysis on any input dataset. It includes custom functions for plotting the data as well as performing different kinds of analyses such as univariate, bivariate and multivariate investigation which is the first step of any predictive modeling pipeline. This package can be used to get … More Introducing xda: R package for exploratory data analysis
Here is topic wise list of R tutorials for Data Science, Time Series Analysis, Natural Language Processing and Machine Learning. This list also serves as a reference guide for several common data analysis tasks. You can also find this list on GitHub where it is updated regularly. The R Language Awesome-R Repository on GitHub R … More Curated list of R tutorials for Data Science
Listed below are codes for some useful operations on Pandas DataFrame: Renaming Columns in Pandas Deleting Columns from pandas DataFrame Adding new Column to existing DataFrame Add one Row in a pandas.DataFrame Changing the order of DataFrame Columns Changing data type of Columns Getting a list of the column headers from a DataFrame Converting list … More Common operations on Pandas DataFrame
I created a list of Python tutorials for data science, machine learning and natural language processing. This list also exists on GitHub where it is updated regularly. The Python Language Dive Into Python Learn Python Wiki on Reddit Highest Voted Python Questions Python Basic Concepts Quick Reference to Python The Elements of Python Style What … More Curated list of Python tutorials for Data Science
I have complied a topic-wise curated list of Machine Learning and Deep Learning tutorials, codes, articles and other resources. See the full list on GitHub.
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