Data Science Pulse
@datascpulse
Welcome to the Data Science Pulse, a one-stop resource for understanding what is happening in the Data Science world at large.
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Python 2 will retire from its 20 years of service in April 2020 python.org/psf/press-rele… #DataScience #MachineLearning #Python
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Help Us Rescue Our Animal Friends in Andros, Greece #crowdfunding @fundrazr Support and Retweet fundrazr.com/AnimalShelterA…
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Help Us Rescue Our Animal Friends in Andros, Greece
https://www.facebook.com/androsanimalsheltergreece
Extended sequence assignment in for loops >>> a, b, c = (1, 2, 3) # Tuple assignment >>> a, b, c (1, 2, 3) >>> for (a, b, c) in [(1, 2, 3), (4, 5, 6)]: # Used in for loop ... print(a, b, c) ... 1 2 3 4 5 6 #Python #DataScience #MachineLearning
Python Dictionaries are: 1. Accessed by key, not offset position 2. Ordered collections of arbitrary objects 3. Variable-length, heterogeneous, and arbitrarily nestable 4. Tables of object references (hash tables) 5. Mutable #DataScience #MachineLearning #Python
Understanding Numpy Axis axis 0 means collapse all rows. axis 1 means collapse all columns. #DataScience #MachineLearning
To count an animal population if you can't catch them all: capture some, mark them, release, and capture again. The ratio of new vs already seen tells you something about the total number. Shown here is iterated mark-and-recapture with a Bayesian updates to belief about pop size
Knowing how to code in Jupyter Notebook is not enough; you need to understand how to write modular code, which follows the time tested software engineering concepts. Moreover, it comes in handy while building machine learning pipelines as well. #DataScience #MachineLearning
The ability to write Pythonic code, to compose modular and loosely-coupled architectures are essential skills. In short, they are as important as knowing machine learning algorithms. #DataScience #MachineLearning
SQL and Data Warehousing concepts are some of the most critical skills that you need to develop. Most people make the mistake of underestimating SQL. It is, therefore, always better to build a solid understanding of these concepts. #DataScience #MachineLearning
Learn Data Science in 2020 with 8 stages. datasciencepulse.com/general/data-s… #Welcome2020 #happynewyear2020 #DataScience
Python 2.7 will retire in another 3 hours and 9 minutes. #DataScience #programming #MachineLearning pythonclock.org
Good read. Also, have a look at the Data Science Roadmap datasciencepulse.com/general/data-s…
Essential Math for #DataScience: Why and How #KDN ow.ly/xNWg30q1Io5
Are you getting confused about where to start their Data Science journey? How to proceed in the Data Science journey? How to make sense of the latest developments happening in the Data Science space? Find your answers below datasciencepulse.com/general/data-s… #DataScience #MachineLearning
Do you think Data Warehousing skills are important for a Data Science stream of work? I think SQL and Data Warehousing are not only important but the key pillars. #DataScience #MachineLearning
SQL is the first and most important step in Data Science journey. Learn SQL thoroughly. #DataScience #MachineLearning #SQL
Data Science Roadmap: Become Fluent in 8 Stages link.medium.com/QyxXzf6BO2 #DataScience #MachineLearning #Python #Programming
There won’t be an AI revolution, but many. What we’re witnessing is only the first one.
There is no intelligence in "Artificial Intelligence" as we know. AI is reduced to more sophisticated rules. #DataScience #MachineLearning
![luketrailrunner's profile picture. ['data science', 'health tech', 'running', 'synthesizers']
not funny enough for twitter, but too edgy for linkedin. opinions are my own. (they/them)](https://pbs.twimg.com/profile_images/1802675860790530048/3R-5U4-9.jpg)
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