What are the top 10 Python libraries for data science toward data science?

In this article, we will discuss top 10 Python Libraries that are used in Data Science namely NumPy, Pandas, Matplotlib, Seaborn, SciPy, Scikit Learn, Statsmodels, TensorFlow, Keras and NLTK. Python is the fastest-growing programming language in the world right now.

Should I put matplotlib on my resume?

Data visualization skills can be highlighted with tools like Matplotlib, Seaborn, and Tableau. Machine learning expertise may include frameworks like TensorFlow and Scikit-learn, while knowledge of big data technologies such as Apache Spark and Hadoop is beneficial for handling large-scale datasets.

Should I put NumPy on a resume?

Here are some guidelines to help you craft a CV that stands out to employers. Highlight Your Python Expertise: Mention your proficiency in Python and related libraries like Pandas, NumPy, and Matplotlib. Include any projects or tasks where you've used Python to analyze data and derive insights.

Should I put Python packages on my resume?

One of the best ways to demonstrate your Python experience is to showcase your Python projects on your resume. You can include projects that you have done for work, school, personal interest, or as part of a course or certification.

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