MSadriAghdam/ML-Zommcamp

Stars
1
Language
Jupyter Notebook
License
MIT License
Created over 3 years ago
Updated about 3 years ago

MSadriAghdam/ML-Zommcamp

MSadriAghdam

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Supply-Chain-Prediction_Neural-Network-ML

In this dataset there are some information about supply chain system of a company and the goal is to predict the best shipment method for new entries.

Jupyter Notebook

Audiobooks-business-case

Neural network machine learning model on a customers dataset.

Jupyter Notebook

Job-adds

Designing a job adds data data analytics model + website for ReDI School of Digital Integration Berlin

Jupyter Notebook

Twitter-Sentiment-Analysis

Sentiment Analysisrefers to the use ofnatural language processing,text analysis,computational linguistics, andbiometricsto systematically identify, extract, quantify, and study affective states and subjective information.

Jupyter Notebook

Absenteeism-Logistic-Regression-Model

To develop a model that will predict the probability of an individual being excessively absent from work.

Jupyter Notebook

Berlin_Flats

Immobilien Scout 24 Dataset, It contains entries from rental flats in Berlin. Lets explore the dataset and find a suitable flat for my friend Josy, who is currently, desperately searching for a new flat in Berlin.

Jupyter Notebook

Plagiarism-finder

A ML model to compare programming and find Plagiarism

Google-stores

A kaggle competition in to predict revenue from online sale on Google store

Jupyter Notebook

Uber_Fare_Pricing

Jupyter Notebook

Neural-Network-on-MNIST-dataset

In this project I built a neural network and trained it using TensorFlow library to recognize handwritten digits using the MNIST dataset.

Jupyter Notebook

MSadriAghdam

bookish-couscous

A-CNN-model--image-classification

A Convolutional Neural Networks on Dogs and Cats dataset (images) to classify them.

Jupyter Notebook

Heart_attack_Prediction

The dataset consist of a group of patients with their medical information and the output (target) describest cases which had a heart attack or not.

Jupyter Notebook