If you are preparing for Machine learning Engineer or Data Scientist or for any data related roles using Python, there are 3 primary libraries that you need
* Pandas
* NumPy
* Matplotlib
In this video, we explore the various frequently asked interview questions for Pandas & NumPy and help you solve them
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Master the Python Libraries for Machine Learning & Data Science here: [ Ссылка ]
Get ready for your next interview, check the tips and tricks here: [ Ссылка ]
Read more about numpy broadcasting technique: [ Ссылка ]
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Why learn #datascience ??
"Data Science is the sexiest job of 21st century"
If you are a #btech student, #diploma in #computerscience, #graduate looking to #career #transition into #datascience , #machinelearning, #dataanalysis, this is a place for you
Everyone of us use social media platforms such as instagram, facebook, or binge watch on OTT platforms such as #youtube , netflix, prime, hotstar or window shop on e-commerce sites such as amazon, flipkart, myntra
It certainly amazes us to see the products of our choice and interest being #recommended to us, our favorite shows being filtered among millions of others
However, not many get to understand how it works. Not to worry, we shall help you understand the concepts in a #simplified and #concise fashion, helping in career transition into machine learning or data science
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Why learn from datahat??
"Datahat is a bridge"
learners --- professionals by simplified data science
It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis
Understand the broad domain of data science and its related subdomains in machine learning, data analysis, data engineering in a self paced, #structured and #guided learning
* Here are few interesting reads on our blog: [ Ссылка ]
* Connect with us on linkedIn: [ Ссылка ]
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Additionally, here are few more useful resources for beginners and curious data enthusiasts
1. kaggle: a platform to learn, practice, compete and win cash prizes [[ Ссылка ]]
2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [[ Ссылка ]]
3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [[ Ссылка ]]
Remember, "the greatest investment ever made is investment in self growth and learning"
