https://github.com/allanotieno254/codsoft
This repository showcases a series of data science projects completed during an internship with CODESOFT. Each project utilizes Python and various machine learning techniques to solve specific problems in data analysis, classification, regression, and predictive modeling.
https://github.com/allanotieno254/codsoft
classification data-analysis data-science feature-engineering machine-learning model-evaluation predictive-modeling python-programming regression
Last synced: about 1 month ago
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This repository showcases a series of data science projects completed during an internship with CODESOFT. Each project utilizes Python and various machine learning techniques to solve specific problems in data analysis, classification, regression, and predictive modeling.
- Host: GitHub
- URL: https://github.com/allanotieno254/codsoft
- Owner: AllanOtieno254
- License: mit
- Created: 2024-06-22T08:07:29.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-06-22T09:43:22.000Z (12 months ago)
- Last Synced: 2025-02-17T08:34:00.270Z (4 months ago)
- Topics: classification, data-analysis, data-science, feature-engineering, machine-learning, model-evaluation, predictive-modeling, python-programming, regression
- Language: Jupyter Notebook
- Homepage: https://colab.research.google.com/?hl=en_GB
- Size: 9.05 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# CODSOFT
## www.codsoft.in
## [email protected]
## https://t.me/codsoft
## LinkedIn: CODSOFT
## Telegram: https://t.me/codsoftt
# If any Query?
## Please feel free to contact -
## Email: [email protected]
## Website: https://www.codsoft.in/
## Internship Tasks in Data Science
# Description Statement
This repository showcases a series of data science projects completed during an internship with CODESOFT. Each project utilizes Python and various machine learning techniques to solve specific problems in data analysis, classification, regression, and predictive modeling.
# Projects
## 1.Titanic Survival Prediction
Predicts survival of passengers aboard the Titanic using machine learning classifiers. Analyzes factors such as age, gender, ticket class, and more.
click to get the dataset:https://www.kaggle.com/datasets/yasserh/titanic-dataset
## 2.Movie Rating Prediction
Estimates the rating of movies based on genre, directors, and actors using regression techniques. Explores features that influence movie ratings.
click to get the dataset:https://www.kaggle.com/datasets/adrianmcmahon/imdb-india-movies
## 3.Iris Flower Classification
Classifies Iris flowers into species (setosa, versicolor, virginica) based on sepal and petal measurements. Demonstrates introductory classification techniques.
click to get the dataset:https://www.kaggle.com/datasets/arshid/iris-flower-dataset
## 4.Sales Prediction using Python
Forecasts product sales considering factors like advertising expenditure and target audience segmentation. Utilizes simple linear regression for prediction.
click to get the dataset:https://www.kaggle.com/code/ashydv/sales-prediction-simple-linear-regression/input
## 5.Credit Card Fraud Detection
Identifies fraudulent credit card transactions using classification algorithms. Addresses data preprocessing, class imbalance, and model evaluation.
click to get the dataset:https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud
# Topics Covered
## Data Science
## Machine Learning
## Predictive Modeling
## Python Programming
## Data Analysis
## Classification
## Regression
## Model Evaluation
## Feature Engineering
# Technologies Used
## Python
## NumPy
## pandas
## scikit-learn
# How to Use
Each project directory contains detailed instructions on setting up and running the code locally. Clone the repository, navigate to the project of interest, and follow the README.md file in that directory for specific guidance.
# License
This repository is licensed under the MIT License. See the LICENSE file for more information.