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Priyanka S Diddi's Projects

autoviz icon autoviz

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

datasist icon datasist

A Python library for easy data analysis, visualization, exploration and modeling

eda-of-titanic-survival-prediction icon eda-of-titanic-survival-prediction

The sinking of the Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the widely considered “unsinkable” RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren’t enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew. While there was some element of luck involved in surviving, it seems some groups of people were more likely to survive than others.

keras-bert icon keras-bert

A simple technique to integrate BERT from tf hub to keras

ktrain icon ktrain

ktrain is a Python library that makes deep learning and AI more accessible and easier to apply

myprojects icon myprojects

Repository about projects or things I do with data :)

prediction-using-supervised-ml-students-performance-prediction icon prediction-using-supervised-ml-students-performance-prediction

The data and problem statement given by "The Sparks Foundation". Nowadays, people are using machine learning in education field also to automate most of the things in return it reduces man power , saves time. In classroom,there are many students and mostly one teacher has to work on students progress so its not always possible to interact with each student and know their progress. Before the final exam,every teacher would like to know their students progress, percentage of marks will secure by his/her students in upcoming exams so that they can work more on weaker students.Here challenge is to predict the percentage of marks of an student based on the number of study hours.

titanic-machine-learning-from-disaster icon titanic-machine-learning-from-disaster

Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics

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