Pinned Repositories
AIML-Capstone
"The capstone project is a focused approach to attempt a real-life challenge with the learnings from the program. The AIML capstone problems are classified under the themes of Computer Vision (CV) and Natural Language Processing (NLP). The goals for either of the projects achieved are tagged here. • CV : Pneumonia Detection - Locate the position of inflammation in an image. • NLP : Automatic Ticket Allocation - Build a classifier that can classify the tickets by analyzing text."
auto-img-capt
Classifying-silhouettes-of-vehicles
Classified vehicles into different types based on silhouettes which may be viewed from many angles. Used PCA in order to reduce dimensionality and SVM for classification
Face-Detection
Recognize, identify and classify faces within images using CNN and image recognition algorithms. In this hands-on project, the goal is to build a face recognition system, which includes building a face detector to locate the position of a face in an image and a face identification model to recognize whose face it is by matching it to the existing database of faces.
Face-Recognition
Face recognition deals with Computer Vision a discipline of Artificial Intelligence and uses techniques of image processing and deep learning. The objective of this project is to build a face recognition system, which includes building a face detector to locate the position of a face in an image and a face identification model to recognize whose face it is by matching it to the existing database of faces.
facemask-Iot
Health-Insurance
This project used Hypothesis Testing and Visualization to leverage customer's health information like smoking habits, bmi, age, and gender for checking statistical evidence to make valuable decisions of insurance business like charges for health insurance.
Identifying-potential-customers-for-loans
Identified potential loan customers for Thera Bank using classification techniques. Compared models built with Logistic Regression and KNN algorithm in order to select the best performing one.
Implementing-a-Image-classification-neural-network-to-classify-Street-House-View-Numbers
SVHN is a real-world image dataset for developing object recognition algorithms with a requirement on data formatting but comes from a significantly harder, unsolved, real-world problem (recognizing digits and numbers in natural scene images). SVHN is obtained from house numbers in Google Street View images. The objective of the project is to learn how to implement a simple image classification pipeline based on the k-Nearest Neighbour and a deep neural network.
obj-follower
sarthak09's Repositories
sarthak09/AIML-Capstone
"The capstone project is a focused approach to attempt a real-life challenge with the learnings from the program. The AIML capstone problems are classified under the themes of Computer Vision (CV) and Natural Language Processing (NLP). The goals for either of the projects achieved are tagged here. • CV : Pneumonia Detection - Locate the position of inflammation in an image. • NLP : Automatic Ticket Allocation - Build a classifier that can classify the tickets by analyzing text."
sarthak09/auto-img-capt
sarthak09/Classifying-silhouettes-of-vehicles
Classified vehicles into different types based on silhouettes which may be viewed from many angles. Used PCA in order to reduce dimensionality and SVM for classification
sarthak09/Face-Detection
Recognize, identify and classify faces within images using CNN and image recognition algorithms. In this hands-on project, the goal is to build a face recognition system, which includes building a face detector to locate the position of a face in an image and a face identification model to recognize whose face it is by matching it to the existing database of faces.
sarthak09/Face-Recognition
Face recognition deals with Computer Vision a discipline of Artificial Intelligence and uses techniques of image processing and deep learning. The objective of this project is to build a face recognition system, which includes building a face detector to locate the position of a face in an image and a face identification model to recognize whose face it is by matching it to the existing database of faces.
sarthak09/facemask-Iot
sarthak09/Health-Insurance
This project used Hypothesis Testing and Visualization to leverage customer's health information like smoking habits, bmi, age, and gender for checking statistical evidence to make valuable decisions of insurance business like charges for health insurance.
sarthak09/Identifying-potential-customers-for-loans
Identified potential loan customers for Thera Bank using classification techniques. Compared models built with Logistic Regression and KNN algorithm in order to select the best performing one.
sarthak09/Implementing-a-Image-classification-neural-network-to-classify-Street-House-View-Numbers
SVHN is a real-world image dataset for developing object recognition algorithms with a requirement on data formatting but comes from a significantly harder, unsolved, real-world problem (recognizing digits and numbers in natural scene images). SVHN is obtained from house numbers in Google Street View images. The objective of the project is to learn how to implement a simple image classification pipeline based on the k-Nearest Neighbour and a deep neural network.
sarthak09/obj-follower
sarthak09/Predicting-the-Strength-of-high-performance-concrete
This project involved feature exploration and selection to predict the strength of high-performance concrete. Used Regression models like Decision tree regressors to find out the most important features and predict the strength. Cross-validation techniques and Grid search were used to tune the parameters for best model performance.
sarthak09/Predicting-the-term-deposit-subscription
Leveraged customer information of bank marketing campaigns to predict whether a customer will subscribe to term deposit or not. Different classification algorithms like Decision tree, Logistic Regression were used. Ensemble techniques like Random forest were used to further improve the classification results.
sarthak09/Product-Recommendation-Systems
This project involved building recommendation systems for Amazon products. A popularity-based model and a collaborative Filtering model were used and evaluated to recommend top-10 products for a user.
sarthak09/Sarcasm-Detection
The goal of this hands on project is to analyse the headlines of the articles from news sources and detect whether they are sarcastic or not.
sarthak09/Sentiment-Analysis
The objective of this project is to build a text classification model which analyses the customer's sentiments based on their reviews in the IMDB database. The model uses a complex deep learning model to build an embedding layer followed by a classification algorithm to analyse the sentiment of the customers.