Bits of Data Science

Free Datacamp Access for 1 Week! 🎉 Hello everyone! I just wanted to share an exciting update - you can access Datacamp's entire library for FREE until September 3rd. Datacamp has thousands of courses, projects, and more to help you learn data skills like Python, R, SQL, data visualization, and machine learning. Don't miss out on this opportunity to skill up for free! Just go to the Datacamp website and start learning:👇 https://www.datacamp.com/freeweek Let your friends know so they can take advantage of this free access too! Data skills are so valuable these days, so make the most of this free week on Datacamp.

You can now perform any Excel operation using Python directly in Excel. Just type =py and start writing your Python code - it will run natively against your Excel data. This eliminates the need to switch between tools or languages."

Announcing Python in Excel: Combining the power of Python and the flexibility of Excel. 📌 Python in Excel is built for analysts. Everyday millions of users around the world rely on familiar Excel tools such as formulas, charts, and PivotTables to analyze and understand their data. Starting today, Python in Excel will also be natively integrated directly into the Excel grid. To get started simply use the new PY function which allows you to input Python code directly into Excel cells. 📌Checkout the complete article here👇: https://techcommunity.microsoft.com/t5/excel-blog/announcing-python-in-excel-combining-the-power-of-python-and-the/ba-p/3893439

📚 5 Free Books on Natural Language Processing to Read in 2023 1. Speech and Language Processing Authors: Dan Jurafsky and James H. Martin 2. Foundations of Statistical Natural Language Processing Authors: Christopher D. Manning and Hinrich Schütze 3. Pattern Recognition and Machine Learning Author: Christopher M. Bishop 4. Neural Network Methods in Natural Language Processing Author: Yoav Goldberg 5. Practical Natural Language Processing That's wrap! Guys if you need any additional resources drop in the comment.

Data Science Cheat sheet👇👇 1. Python 2. Jupyter 3. Numpy 4.Scipy 5.Pandas 6.Scikit -Learn 7.Matplotlib 8.Seaborn 9.Bokeh That's wrap!

21 Interview Questions for SQL 📊 1) What is SQL and why should we use SQL? 2) What is Database and Table? 3) Difference between Primary and Unique key? 4) Difference between Drop, Truncate and Delete? 5) What is a Foreign key of a database table? 4) Is it possible to create a primary key as a non-clustered index? If so, why might you need to do this? 5) What is Joins and Join Type, equi-join, Cross join, Self join? 6) How to change a table name in SQL? 7) What is a DEFAULT constraint? 8) Difference between Triggers, Function and Stored Procedure 9) What is an index? 10) Explain the types of index? 11) What is a data warehouse? 12) State the differences between clustered and non-clustered indexes 13) What is the ACID property in a database? 14) What do you understand about a character manipulation function? 15) What are views? Give an example. 16) State the differences between views and tables. 17) What is a database cursor? How to use a database cursor? 18) Difference between ROWNUM and ROWID? 19) what is Materialized View? 20) What is the Subquery? 21) Most important Question is :-- performance tuning?

Data Science In A Nutshell

How does a Transformer generate text?