Discover fares-ds/pandas Open Source project

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Full data analysis and data visualization projects notebooks using Pandas, Numpy, matplotlib and seaborn

Predicting-the-closing-stock-price-of-APPLE-using-LSTM

In this project we will be looking at data from the stock market, particularly some technology stocks. We will learn how to use pandas to get stock information, visualize different aspects of it, and finally we will look at a few ways of analyzing the risk of a stock, based on its previous performance history.

Jupyter Notebook

Data-Science-Projects-From-Kaggle

Data science projects from the Kaggle website: Data Analysis, Data Visualization, Machine Learning, Time Series Analysis, Computer Vision, Natural Language Processing, Predictive Modeling ...

Jupyter Notebook

beginner_python_projects

This repository contain 10 python friendly projects for bigenner to start learning python by building projects.

Python

Minimizing-Churn-Rate-Through-Analysis-of-Financial-Habits

The objective of this model is to predict which users are likely to churn, so that the company can focus on re-engaging these users with the product. These efforts can be email reminders about the benefits of the product, especially focusing on features that are new or that the user has shown to value.

Jupyter Notebook

Predicting_Loan_Defaulters_Using_Deep_Learning

In this case study, we will also develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers.

Jupyter Notebook

Machine-Learning-Algorithms-Tutorials

Basic Machine Learning Algorithms tutorials (Linear Regression, Logistic Regression, SVM, Random Forest, Bagging, KNN, K-Means ...)

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Natural-Language-Processing

Natural Language Processing projects and Tutorials

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IBM_HR_Analytics_Employee_And_Performance

Predict attrition of your valuable employees

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machine_learning_in_python_with_scikit_learn

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Fashion-Class-Classification

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Using-Gradient-Boosting-for-Time-Series-prediction-tasks

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Machine_Learning_Deployment_with_Streamlit

In this project, I used data from a Kaggle competition and build machine learning models to classify a text as Disaster or Not. The model is deployed on Heroku.

Python

Business-Case-Study---Absenteeism

Jupyter Notebook

Natural_Language_Processing_Sentiment_Analysis

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MNIST-Handwritten-Digit-Recognition

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data_analysis_in_python_with_pandas

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Directing-Customers-to-Subscription-Through-App-Behavior-Analysis

The objective of this model is to predict which users will not subscribe to the paid membership so that greater marketing efforts can go into trying to "convert" them to paid users.

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House-price-prediction-Kaggle-Competition

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SIIM-ISIC-Melanoma-Classification

Identify melanoma in lesion images Kaggle Competition

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Business-Case-Study-Audiobook-app

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Algorithms_and_data_structures

Python

Data-Science-BEST-practices

Data science and EDA best practices using Pandas

Jupyter Notebook

Euler_Problems

Python

Predicting-heart-disease-using-machine-learning

Experiments with the Cleveland database have concentrated on simply attempting to distinguish presence (values 1,2,3,4) from absence (value 0). See if you can find any other trends in heart data to predict certain cardiovascular events or find any clear indications of heart health.

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Real-or-Not-NLP-with-Disaster-Tweets

Predict which Tweets are about real disasters and which ones are not

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Natural-Language-Processing-with-Python

Can you use this dataset to build a prediction model that will accurately classify which texts are spam?

Jupyter Notebook

Cifar-10_Image_Classification_Using_CNNs

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

Jupyter Notebook

Time_Series_Analysis_Tutorial

A time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time.

Jupyter Notebook

CoderByte

Python

Credit-Card-Fraud-Detection

The Credit Card Fraud Detection Problem includes modeling past credit card transactions with the knowledge of the ones that turned out to be a fraud. This model is then used to identify whether a new transaction is fraudulent or not. Our aim here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications.

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data_visualization

Python

web_page_dashboard

Python

Automobile_Consulting_Company_Predicting_Cars_Prices

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Blue-Book-for-Bulldozers-Kaggle-Competition

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Malaria_Cell_Classification_Using_CNNs

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Git_and_GitHub_Tutorial

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Predicting-the-Likelihood-of-E-Signing-a-Loan-Based-on-Financial-History

Develop a model to predict for 'quality' applicants are those who reach a key part of the loan application process.

Jupyter Notebook

Telecom_Customer_Churn_Prediction

Predict behavior to retain customers. You can analyze all relevant customer data and develop focused customer retention programs.

Jupyter Notebook

Computer_Vision_with_OpenCV_and_TensorFlow

Jupyter Notebook

talk-to-youtube-videos

Youtube assitant using OpenAI, Langchain, and FastAPI - Using this API you can ask questions directly to your favorate podcast.

Python

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