ABHIJITH K S's Projects
Questions from 2016-2020 classified in three categories based on their quality
this repo contains some very useful lust know python features
Config files for my GitHub profile.
Resume web app
My efforts to do certifications in major cloud, other services
1. Load the attached csv file in python. Each row consists of feature 1, feature 2, class label. 2. Train two single/double hidden layer deep networks by varying the number of hidden nodes (4, 8, 12, 16) in each layer with 70% training and 30% validation data. Use appropriate learning rate, activation, and loss functions and also mention the reason for choosing the same. Report, compare, and explain the observed accuracy and minimum loss achieved. [0.5+1 mark] 3. Visually observe the dataset and design an appropriate feature transformation (derived feature) such that after feature transformation, the dataset can be classified using a minimal network architecture (minimum number of parameters). Design, train this minimal network, and report training and validation errors, and trained parameters of the network. Use 70% training and 30% validation data, appropriate learning rate, activation and loss functions. Explain the final results.
Fridge App is a web-based application that allows users to keep track of the contents of their fridge. It is intended for anyone who wants to reduce food waste and stay organized in the kitchen.
A robot powered training repository :robot:
Using the state o the art BERT model to create a text classification model
Learn how to responsibly develop, deploy and maintain production machine learning applications.
This repo contains important information about markdown files that will be helpful while creating documentations
A project-based course on the foundations of MLOps to responsibly develop, deploy and maintain ML.
This is the repo for the Udemy Course Python Dashboards with Plotly's Dash
This is guide to launch a PySpark session in Raspberry pi 4
Python Deep Dive Course - Accompanying Materials
This is an analysis on diiffernt machine learning techniques that can be used in predicting whether a customer will make purchase in the next selected time frame
A BERT model for scientific text.
The SMS Spam Collection is a set of SMS tagged messages that have been collected for SMS Spam research. It contains one set of SMS messages in English of 5,574 messages, tagged according to being ham (legitimate) or spam.
Solutions to Problems For SQL on Leetcode, Hackerrank & DataLemur
Contains important SQL queries