rajvardhan7 Goto Github PK

-mlproject

any_date_column_extractor

Concept of NLP and mattern has been leveraged

autonomous-driving-using-yolo

YOLO uses grid approach for object detection which makes it faster than sliding window or R-CNN methods

autonoumous-car-driving-system

YOLO algorithm which uses grid approach has been used

chatbot

this bot is a multipupose bot. It can talk , filter spam etc.

ci1

Attempting Continuous Integaration On ML project

ci2

attempt 2

ci3

client-server-model

Python based client Server System

deep-neural-network-using-tensorflow

The basics of Tensor flow framework can be learnt through this Andrew NG's assignment

emotion-detection-using-keras

ensemble

food101tm-using-tensorflow

started from simple tiny VGG using subset of data (only 10 classes) with accuracy of 0.3 to a model leveraging transferlerning. Came close to deepfood score

html-files

institute-website

ml-service

my ml serives

music_of_ai

The project is aimed at creating a 500 notes long music using LSTM network

nodal-point-analysis-bottom-hole-

Operational Point is obtained using linear IPR model and Poettmann–Carpenter’s TPR model

optimizers

mini batch gradient descent,momentum,ADAM

pressure-buildup-test-analsis

PBU test data taken from Tarek Ahmed

rajvardhan7.github.io

real-time-object-detection-with-opencv-and-cpu-

restrau_classifier_usingnlp_and_pycaret

The shortest way for comparing 13 classifiers is possible using a very robust package called Pycaret. The project shows a demonstration of classifying a review as a positive or a negative

segregator

Can segregate numeric variables, categorial variables and useless ID like variables for any dataset

tarners-method-using-python

tarners-method-with-python

To make it more robust a general correlation is obtained by fitting XGB model on givel rel_perm data

tensorflow

The motive is to learn and cover all the tensorflow stuff and become a certified developer

text_summarizer-with-tf-idf

textile-detection

Fabric defect detection is a necessary and essential step of quality control in the textile manufacturing industry. It is the determination process of the location, type and size of the defects found on the fabric surface.

well_deliverability_nodal_point_analysis_with_python

NewtonRaphson error method is leveraged