Introduction of Python:
Python is quite a good language for fast prototyping. It has a huge amount of high quality and open source libraries. And I want to reuse several of them.
Numpy Numpy is a linear algebra library to work with dimensional arrays, which contains useful linear algebra routines and random number capabilities.
Pandas Pandas is a library providing fast, flexible, and expressive way to work with a relational or table of data, both easily and intuitive. It allows you to process your data in a way similar to SQL. Scikit-learn is a library of classic machine learning algorithms. It features various classification, regression, and clustering algorithms, including support virtual machines, random force, and a lot more.
Matplotlib Matplotlib is a plotting library. It allows you to do a variety of visualization, like line plots, histograms, scatter plots and a lot more.
Keras Keras is a user-friendly framework for neural nets. This new package is an efficient implementation of this new ]projection method which we will discuss in our course.
References: LINKS
-Solve kaggle's House Prices -Predict House Prices ~ Challenge the Kaggle House Price Tutorial -How to use LabelEncoder of scikit-learn -Solve Kaggle's Regression and become Kaggler
Overview of methods(Documentations)
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