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1
4
2
Python allows you to
perform various statistical
tests and analyses, helping
you extract meaningful
information from data.
5
DATA CLEANING AND
PREPROCESSING:
Raw data is often messy. You
will learn how to clean,
transform, and preprocess
data to ensure it is suitable
for analysis. Python’s pandas
library is indispensable for
these tasks.
EDA involves visualizing and
summarizing data to uncover
insights. Python’s Matplotlib
and Seaborn libraries provide
a rich toolkit for creating
informative graphs and plots.
3
Machine learning is a core
component of data science.
Python’s scikit-learn library
offers a plethora of algorithms
for tasks like classification,
regression, and clustering.
DEEP LEARNING:
If you are interested in cutting-edge
AI, Python’s TensorFlow and PyTorch
libraries are your go-to tools for deep
learning projects.
PYTHON FOR DATA
SCIENCE
KEY CONCEPTS
EXPLORATORY DATA ANALYSIS
(EDA):
STATISTICAL ANALYSIS:
MACHINE LEARNING:
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Best practices of a Python developers (2).pdf

  • 1. 1 4 2 Python allows you to perform various statistical tests and analyses, helping you extract meaningful information from data. 5 DATA CLEANING AND PREPROCESSING: Raw data is often messy. You will learn how to clean, transform, and preprocess data to ensure it is suitable for analysis. Python’s pandas library is indispensable for these tasks. EDA involves visualizing and summarizing data to uncover insights. Python’s Matplotlib and Seaborn libraries provide a rich toolkit for creating informative graphs and plots. 3 Machine learning is a core component of data science. Python’s scikit-learn library offers a plethora of algorithms for tasks like classification, regression, and clustering. DEEP LEARNING: If you are interested in cutting-edge AI, Python’s TensorFlow and PyTorch libraries are your go-to tools for deep learning projects. PYTHON FOR DATA SCIENCE KEY CONCEPTS EXPLORATORY DATA ANALYSIS (EDA): STATISTICAL ANALYSIS: MACHINE LEARNING:
  翻译: