Abishek Arunachalam's repositories
Algorithmic_toolbox
Greedy algorithms, divide and conquer strategy and dynamic programming approaches for building scalable data products.
ASX-200---Ploty-visualisation
A Plotly data visualisation with update menu and two traces for the ASX 200 data.
awesome-deep-learning-papers
The most cited deep learning papers
Capture-Platform-Event-Logs
The scripts establishes connection and inserts platform event logs in a JSON file to a MySQL database
course
The Hugging Face course on Transformers
Credit-Risk-Analysis
The project aims to create a binary classification model that can accurately classify credit risk case and non-credit risk case.
FinancialNewsSummariser
Ingest financial news data in real-time using Kafka publisher subscriber. Summarise the news and send alerts to the user to support investment decisions.
FlightTravelAnalytics
A Scala based Apache-Spark project for data processing and analysis
folium
Python Data. Leaflet.js Maps.
Forecasting-GDP-of-Australia
Forecasting GDP of Australia based on economic indicators that substitute the GDP formula (GDP= Consumption or Consumer spending (C) + Government spending (G) + Investment of country (I) + Business capital expenditures (NX)).
Image-Captioning--Deep-Learning-model
Automatic labelling of images by using a combination of Convolution Neural Network (CNN) to identify objects in the images and Long-short Term Memory (LSTM) a variant of Recurrent Neural Network(RNN) for labelling of images.
Image-classification-with-Convolutional-Neural-Network
The project involves working with the famous Mnist fashion dataset to classify clothes in each category using Convolutional Neural Networks (CNN). In the part-1, transfer learning is performed by using the RESNET-50 model weights from the Keras package and classify the images. In part-2, CNN model is build from scratch by stacking layers and training on the dataset.
LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
GenerativeAIWithLLM
Fine tuning LLM on custom dataset using memory efficient fine-tuning and soft prompting
LSTM-Human-Activity-Recognition
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo). Classifying the type of movement amongst six activity categories - Guillaume Chevalier
reinforcement-learning-an-introduction
Python implementation of Reinforcement Learning: An Introduction
rstudio2019
Resources from my Rstudio::conf 2019 talk
Vanilla-Neural-Network
This project aims at developing a vanilla neural network from scratch using NumPy arrays and matrix operations.