I will do python data science, machine learning and data engineering projects
I will do python data science, machine learning and data engineering projects
There are many “detection” projects you can do with Python. Instead of just naming one, I’m going to list by the level of difficulty those I implemented with Python. 2. Fake News Detection.
Get I will do python data science, machine learning and data engineering projects
There are several popular Python libraries for data science. Some of the most widely used libraries include:
- Pandas: This library is used for data manipulation and analysis. It provides data structures for efficiently storing large datasets and tools for working with them.
- NumPy: This library is used for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a large collection of mathematical functions to operate on them.
- Matplotlib: This library is used for data visualization in Python. It provides a wide range of tools for creating charts, graphs, and other visualizations.
- Seaborn: This library is built on top of Matplotlib and provides additional tools for creating more complex visualizations.
- scikit-learn: This library is used for machine learning in Python. It provides a wide range of algorithms for classification, regression, clustering, and more.
- SciPy: This library is used for scientific computing in Python. It provides a wide range of tools for optimization, integration, interpolation, linear algebra, and more.
- Keras: This library is used for deep learning in Python. It provides a high-level interface to TensorFlow that makes it easier to build and train deep neural networks.
There are several popular Python libraries for machine learning. Some of the most widely used libraries include:
- NumPy: This library is used for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a large collection of mathematical functions to operate on them.
- Scikit-learn: This library is built on top of NumPy and provides a wide range of algorithms for classification, regression, clustering, and more.
- Pandas: This library is used for data manipulation and analysis. It provides data structures for efficiently storing large datasets and tools for working with them.
- Theano: This library is used for deep learning in Python. It provides support for creating and training deep neural networks.
- TensorFlow: This library is used for deep learning in Python. It provides a wide range of tools for building and training deep neural networks.
- Keras: This library is used for deep learning in Python. It provides a high-level interface to TensorFlow that makes it easier to build and train deep neural networks.
Some of the most popular Python libraries for data engineering include:
- Pandas: This library is used for data manipulation and analysis. It provides data structures for efficiently storing large datasets and tools for working with them.
- Apache Airflow: This library serves as a platform for data engineers to author, schedule, and monitor workflows.
- Pyparsing: This library is used to eliminate the need to manually craft a parsing state machine.
- TensorFlow: This library is used for deep learning in Python. It provides a wide range of tools for building and training deep neural networks.
- Scikit-learn: This library is built on top of NumPy and provides a wide range of algorithms for classification, regression, clustering, and more.
- Beautiful Soup: This library is used for web scraping and parsing HTML and XML documents.
These libraries provide data engineers with a wide range of tools to work with, helping them manipulate, transform, and store data faster and more effectively12.
Basic : $5
Standard : $20
Premium : $40
Simple data analysis, data preprocessing and machine learning task for small dataset
I will do python data science, machine learning and data engineering projects | Fiverr
