English | Size: 433.11 MB
Genre: eLearning
Learn
Use Python for data mining, loading, and manipulation
Understand simple statistics and probability using NumPy
Work with Bayesian statistical analysis with NumPy library
Perform statistical modeling and fitting using the NumPy, SciPy, and statsmodels libraries
Use Python’s graphics libraries to plot data with the Matplotlib library
Work with the scikit-learn library to build AI models
About
Python has grown into a key language that can be used to develop solutions for a variety of data science challenges. This course will teach you the fundamentals of data science using Python and its growing collection of libraries that focus on particular elements of data science.
In this course, we will get hands-on with a variety of data science tasks. After a quick primer on Python, you will start with a quick task: sourcing, processing, and cleaning a dataset. Then, you will use Python to mine data from its source and analyze available data via statistical and probability analysis techniques by using NumPy and pandas. You will also look at modeling data in order to perform Artificial Intelligence prediction by using the SciPy, scikit-learn, and statsmodels libraries. The course also covers visualization methods using the Matplotlib library to display this analysis and visually demonstrate patterns in the data.
By the end of this course, you will be able to work on data science tasks in a practical way with different Python libraries and achieve your goals.
The code files for this course are available at –
https://github.com/PacktPublishing/Fundamentals-of-Data-Science-with-Python-
Features
Use Python with a variety of libraries to get deeper insights from your data
Address data science challenges with Python and its extensive collection of libraries along with practical examples that you can implement
Gain the key skills and understanding you need to start integrating and developing Python-based solutions into your own data science activities
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