Name: TEJAS PHASE
Type: User
Company: Electronics Engineer
Bio: Experimenter| Practitioner | Regression Analysis | Classification Tasks| Vision Based Models | Image Processing | Enterprise Design Thinking in AI Designs
Location: SATARA,MAHARASHTRA,INDIA.
Blog: https://www.linkedin.com/in/tejasphase/
TEJAS PHASE's Projects
This is daily concept practice project include tasks of Importing the dataset, Cleaning it, Analyze it then Model Building and Evaluation.
This repository is a demonstration of building a Convolution Neural Network from Scratch in Python without any usage of the External Library.
This is Experimentation Repository.
The project is the demonstration of building CNN for Identifying the Cat or Dog images.
The project is focused on building Classification Model using Convolution Neural Network for classifying the images into "Horse" and "Human".
This is second project to push through NetBeans
A combination of Data Science and Machine Learning techniques to predict ratings of a particular movie based on input features.
A Machine Learning Project for Prediction of the one's Income Level based on different features.
This repository contains all the basic operations that can be implemented on an image to process and analyse it.
This repository contains notebook which contains all the implementations of Non_linear activation functions and their derivatives.
The project is the demonstration of building the Convolution Neural Network from scratch and compared its accuracy over simple Neural Network.
The repository is the effort to explain useful NumPy commands in the tasks of Data Cleaning & Data Preparation in Exploratory Data Analysis step. The commands are explained in detail with appropriate examples. The one who will go with the notebooks in both parts will get knowledge about the importance of the Numpy library in Data Analysis and how it can be useful to perform various treatments on Data. So, without wasting more time let's jump into NumPy's World.
This is an experimentation with H2O AutoML library for Data Pre-processing and Model Selection.
A Jupyter Notebook showcasing an implementation of Bike Share Analysis Project.
In this project I built a simple neural network for classifying clothing items from Fashion MNIST dataset and perform experimentation with the model parameters to analyze the effect on model's accuracy.
Face Detection and Eye Detection using HAAR-CASCADE Classifier in still images as well as in Video.