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Featured Projects

Ajay Pratap

We will see how to model a deep learning network which can classify flowers into “roses” and “daisies”. This is a toy dataset and its purpose is to introduce you to the key concepts and methodologies.

Ajay Pratap

In this Kaggle Competition, we need to predict the number of incidents in specific areas of Dubai. The final goal is to reduce the waiting time for the patrols. But in order to do so, we need to predict when and where the incidents will take place.

Ajay Pratap

The objective of this project is to learn various techniques we can for video classification

We will see how to model a deep learning network which can classify flowers into “roses” and “daisies”. This is a toy dataset and its purpose is to introduce you to the key concepts and methodologies.

Regression is a handy tool to find relationships between dependent variables and independent variables. However, we cannot always fit a regression line to any given dataset. The objective of this notebook is to provide core concepts of Linear Regression analysis.

This project explains the use of feature engineering, Feature selection, model training, model selection, VIF and model evaluation in the context of Simple linear regression

In this Covid19 Data Analysis Notebook, we will try to explore data available from open source to identify how Covid19 is impacting happiness in a country.

This Kaggle Competition is to detect functional tissue units (FTUs) across different tissue preparation pipelines. An FTU is defined as a “three-dimensional block of cells centred around a capillary, such that each cell in this block is within diffusion distance from any other cell in the same block”. The goal of this competition is the implementation of a successful and robust glomeruli FTU detector.

Neural networks have revolutionised image processing in several different domains. Among these is the field of medical imaging. In this notebook, we will get some hands-on experience in working with Chest X-Ray (CXR) images.

The objective of this exercise is to identify images where an “effusion” is present. This is a classification problem, where we will be dealing with two classes – ‘effusion’ and ‘no finding’. Here, the latter represents a “normal” X-ray image.

In this case study, we will apply EDA (Exploratory Data Analysis) Techniques to develop an understanding risk analytics and financial service. With this EDA, we will try to understand how to minimise the risk of losing money while lending money to customers.

In this Kaggle Competition, we need to predict the number of incidents in specific areas of Dubai. The final goal is to reduce the waiting time for the patrols. But in order to do so, we need to predict when and where the incidents will take place.

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