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Benign-Malignant Prediction

Description

A lot of unnecessary anguish and surgery arises from false positives arising from mammogram results. If we can build a better way to interpret them through supervised machine learning, it could improve a lot of lives.

Built with

  • pandas - is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive.
  • numpy - NumPy is a python library used for working with arrays. It also has functions for working in domain of linear algebra, fourier transform, and matrices.
  • scipy - The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation.
  • joblib - Joblib is a set of tools to provide lightweight pipelining in Python.
  • scikit-learn - scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
  • matplotlib - Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
  • seaborn - Seaborn is a library for making statistical graphics in Python. It is built on top of matplotlib and closely integrated with pandas data structures.
  • tensorflow - TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
  • Keras - Keras is a high-level neural networks API for Python.

Prerequisites

You should have Python3 and Anaconda installed in your system. To install other required libraries, run the following command in the terminal.

pip install -r requirements.txt

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