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appliedplotting_assignment4

breast_cancer_detection_using_python_and_machine_learning

In this project, the machine learning model is trained on the breast cancer dataset and gives approximate accuracy of 96%.

chronic_kidney_disease_prediction_using_python_and_ann

Chronic kidney disease prediction done using Artificial Neural Network.

classify_handwritten_digits_using_python_and_ann

Hand written digits classification done on MNIST dataset images as 0-9 numbers

classify_iris_species_using_python_and_logistic_regression

The project for the iris species classification using logistic regression

continuous-delivery-with-docker-and-jenkins-second-edition

Continuous Delivery with Docker and Jenkins Second Edition, published by Packt

explore_nba_data_with_kmeans_clustering

Exploring NBA dataset using KMeans clustering. The dataset is also included in the repository.

heart_disease_detection_using_python_and_machine_learning

This program classifies a person depending on the data, whether he is having cardiovuscular disease or not. The dataset is also included in the dataset.

make_interactive_candlestick_charts_on_amazon_stock_prices

This program shows how to create an interactive candlestick chart in python using Plotly.

phase_2

pneumonia_detection

In this project, the pneumonia detection is done on the image dataset. The image data is directly imported from kaggle and uploaded to the Google Colaboratory. The notebook includes the code to import the dataset from kaggle and use it for training the model on the colaboratory. If the dataset is available on your system, please skip the cells that include the functions to import the dataset from kaggle and then unzipping it on colab. The link for the dataset is in READ_ME file below.

predict_boston_house_prices_using_python_and_linear_regression

The Linear regression model is implemented on Boston house prices dataset.

prediction_using_decision_tree_classifier

As a part of the Data Science and Business Analytics internship, the task was to make predictions on the iris dataset using decision tree.

python_for_finance

This is a python program for finance. It shows how to commpute portfolio simple returns, get daily returns and volatility etc. The graphs are also present in the notebook.

titanic_survival_prediction_using_machine_learning

Predicting the survival chances of a passenger using titanic dataset from kaggle.

umls23

week6