Python and Libraries
Our courses are designed using Python and it’s vast repository of libraries. Python has a rich ecosystem of libraries and tools for data science and machine learning.
Here are some of the most commonly used Python libraries for data science and machine learning:
Data Exploratory / Processing
NumPy – A library for working with arrays and matrices, which is useful for numerical operations and scientific computing.
Pandas – A library for data manipulation and analysis that provides tools for reading and writing data, as well as data cleaning, merging, and reshaping
PySpark – A library for big data processing and distributed computing that provides tools for working with large datasets in a distributed environment.
NLTK – A natural language processing library that provides tools for processing human language data, such as text and speech.
SciPy – A library for scientific computing that provides tools for optimization, integration, interpolation, and signal processing.
Machine Learning
Scikit-learn – A machine learning library that provides algorithms for regression, classification, clustering, and dimensionality reduction.
TensorFlow – An open-source platform for building and training machine learning models, developed by Google.
Keras – A high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano.
PyTorch – An open-source machine learning framework that provides an easy-to-use interface for building and training neural networks.
XGBoost – A library for gradient boosting that provides tools for building and tuning high-performance machine learning models.
LightGBM – A library for gradient boosting that provides tools for building and optimizing high-performance machine learning models.
Gensim – A library for natural language processing and topic modeling that provides tools for text preprocessing, document clustering, and semantic analysis.
Visualization
Matplotlib – A plotting library that provides a variety of graphs and charts for visualizing data.
Seaborn – A visualization library that provides high-level interface for creating informative and attractive statistical graphics.
Plotly – A visualization library that provides interactive charts and graphs for web-based data visualization.
Bokeh – A visualization library that provides interactive visualizations for web-based data visualization.
Python and Libraries
Python as a language and some of the popular libraries for Data Science and Machine Learning
These libraries are just a few examples of the many powerful tools available in Python for data science and machine learning.
We shall introduce/use the required libraries as we pick up a course or a topic.
