⚠️ Daily Python Facts ⚠️

Checking whether any element in the sequence is Truthful.

>>> any(a % 2==0 for a in range(0,10,2))
True

- @pythonpool -

Facebook #Pytorch has launched own 📘 Book.

Grab your free copy. This is for limited time period only.

#DeepLearning with #PyTorch provides a detailed, #hands-on introduction to #building and #training #neuralnetworks with PyTorch, a popular open source machine learning framework. This book includes:

Introduction to deep learning and the PyTorch library 📚 Pre-trained networks 📚 Tensors 📚 The mechanics of learning 📚 Using a neural network to fit data

Get a free copy for a limited time. 📘 Book Page Link : https://pytorch.org/deep-learning-with-pytorch

⚠️ Daily Python Facts ⚠️

Return Multiple values to Python

# Multiple Return Values in Python!
def func():
return 1, 2, 3, 4, 5
one, two, three, four, five = func()
print(one, two, three, four, five)

Output: (1, 2, 3, 4, 5)

- @pythonpool -

Develop🚀 Deep Learning Models on #Theano and #Tensorflow using #Keras by Jason Brownlee
Machine Learning Mastery

⚠️ Daily Python Facts ⚠️

In Python, everything is done by reference. It doesn’t support pointers like C++.

Unlike other programming languages, Python does not support pointers. Instead, objects are passed by reference.

- @pythonpool -

List of Free Natural Language Processing Courses

1)Speech and Language Processing by Dan Jurafsky and James Martin
https://web.stanford.edu/~jurafsky/slp3/

2) Deep Learning for Natural Language Processing by Richard Socher (Stanford University)
https://m.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6

3. Natural Language Processing (NLP) by Microsoft
https://www.edx.org/course/natural-language-processing-nlp-2

4. Andrew Ng’s course on Machine Learning
https://www.coursera.org/learn/machine-learning/home/welcome

5. The video lectures and resources for Stanford’s Natural Language Processing with Deep Learning
http://web.stanford.edu/class/cs224n/

https://m.youtube.com/playlist?list=PL3FW7Lu3i5Jsnh1rnUwq_TcylNr7EkRe6


6. Sequence Models for Time Series and Natural Language Processing 
https://www.coursera.org/learn/sequence-models-tensorflow-gcp?ranMID=40328&ranEAID=SAyYsTvLiGQ&ranSiteID=SAyYsTvLiGQ-ACNikbtJvh2d5Evme5yZQA&siteID=SAyYsTvLiGQ-ACNikbtJvh2d5Evme5yZQA&utm_content=10&utm_medium=partners&utm_source=linkshare&utm_campaign=SAyYsTvLiGQ

7. Deep Natural Language Processing course offered in Hilary Term 2017 at the University of Oxford.
http://www.cs.ox.ac.uk/teaching/courses/2016-2017/dl/

8. Natural Language Processing Fundamentals in Python by Datacamp
https://www.datacamp.com/courses/natural-language-processing-fundamentals-in-python

9 Natural Language Processing by Higher School of Economics
https://www.coursera.org/learn/language-processing?

10 How to Build a Chatbot Without Coding by IBM
https://www.coursera.org/learn/building-ai-powered-chatbots

11. CS 388: Natural Language Processing by University of Texas
https://www.cs.utexas.edu/~mooney/cs388/

12. Natural Language Processing with Python
http://www.nltk.org/book/

13. CSEP 517: Natural Language Processing by University of Washington
https://courses.cs.washington.edu/courses/csep517/17sp/

14. Dan Jurafsky & Chris Manning: Natural Language Processing
https://m.youtube.com/playlist?list=PL8FFE3F391203C98C

15. NATURAL LANGUAGE PROCESSING by Carnegie Mellon University
http://demo.clab.cs.cmu.edu/NLP/

16. CS224n: Natural Language Processing with Deep Learning by Stanford University
http://web.stanford.edu/class/cs224n/


Note: If you find some more Natural Language Processing courses which are free then please feel free to send us via email. Our email is [email protected]

Do Share our Channel @pythonpool ❤️ For more

⚠️ Daily Python Facts ⚠️

BeautifulSoup

BeautifulSoup is a great python library. It is used for parsing. It can parse different broken HTML and XML documents, as well. It offers an easy way for web scraping by extracting direct data from HTML. Many professionals are really happy with its amazing performance. It can save quite a lot of time on your day.

- @pythonpool -

TOP 15 PYTHON RESOURCES

1) Learn Python the Hard Way (free ebook)
https://learnpythonthehardway.org/book/

2)Codecademy (free code tutorials)
https://www.codecademy.com/learn/learn-python

3)Google's Python class 
https://developers.google.com/edu/python/

4)A Byte of Python (free ebook)
https://python.swaroopch.com

5)TutsPlus tutorial
https://code.tutsplus.com/articles/the-best-way-to-learn-python--net-26288

6)LEARN PYTHON ONLINE: BEST PYTHON
https://mikkegoes.com/learn-python-online-best-resources/

7)Best Python Resources for Beginners and Professionals
https://pythontips.com/2013/09/01/best-python-resources/amp/

8)TutorialsPoint
http://www.tutorialspoint.com/python/

9)Learning Python
https://docs.python-guide.org/intro/learning/

10)Full Stack Python
https://www.fullstackpython.com/best-python-resources.html

11)Python For Beginners
https://www.python.org/about/gettingstarted/

12)Codementor community
https://www.codementor.io/community/topic/python

13)How should I start learning Python?
https://www.quora.com/How-should-I-start-learning-Python-1

14)Codeconquest
https://www.codeconquest.com/blog/the-50-best-websites-to-learn-python/

15)Python Pool
https://www.pythonpool.com

⚠️ Python Daily Facts ⚠️

FlashText

FlashText is another python library that offers easy search and replacement of words from documents. All FlashText needs is a set of words and string. Then it identifies some words as keywords and replaces them from Text Data. It is a very effective library. People who are struggling with word replacement can choose it with confidence.

- @pythonpool -

⚠️ Daily Python Facts ⚠️

Arrow
Arrow is a practical python library. It is a friendly library that basically works with dates and times. Arrow comes with a smart API. This API supports many general schemes. It is an interesting library. Beginners with basic knowledge of coding can get pretty well with Arrow.

- @pythonpool -

One of the most common questions people ask is which IDE/environment/ tool to use while working on your data science/AI projects. As you would expect, there is no dearth of options available – from language-specific IDEs like R Studio, PyCharm to editors like Sublime Text or Atom – the choice can be intimidating for a beginner.

If there is one tool that every data scientist should use or must be comfortable with, it is Jupyter Notebooks. Jupyter Notebooks are powerful, versatile, shareable and provide the ability to perform data visualization in the same environment. Jupyter Notebooks allow to create and share documents, from codes to full-blown reports and most important is that its Open-Source. so sharing official Jupyter Notebook Documentation

⚠️ Python Daily Facts ⚠️

OpenCV Python
OpenCV, a.k.a Open Source Computer Vision is a python package for image processing. It monitors overall functions that are focused on instant computer vision. Although OpenCV has no proper documentation, according to many developers, it is one of the hardest libraries to learn. However, it does provide many inbuilt functions through which you learn Computer vision easily.

- @pythonpool -

⚠️ Python Daily Facts ⚠️

Numpy
Numpy is a popular array – processing package of Python. It provides good support for different dimensional array objects as well as for matrices. Numpy is not only confined to providing arrays only, but it also provides a variety of tools to manage these arrays. It is fast, efficient, and really good for managing matrice and arrays.

- @pythonpool -

⚠️ Daily Python Facts ⚠️

Pillow
Pillow is actually a fork of PIL – Python Image Library. At first, pillow was mainly based on the PIL code-structure. But later, it transformed into something more friendly and better. Experts say Pillow is actually a modern version of PIL. However, pillow is your trusted company while working with images or any type of image format.

- @pythonpool -

⚠️ Daily Python Facts ⚠️

Reverse the order of the fruit list:

fruits = ['apple', 'banana', 'cherry']
fruits.reverse()
print(fruits)

Ouput:
['cherry', 'banana', 'apple']

- @pythonpool -

⚠️ Daily Python Facts ⚠️

It is also possible to use the list() constructor to make a new list.

thislist = list(("apple", "banana", "cherry"))
print(thislist)

Output:
['apple', 'banana', 'cherry']

- @pythonpool -

⚠️ Daily Python Facts ⚠️


It is also possible to use the dict() constructor to make a new dictionary

thisdict = dict(brand="Ford", model="Mustang", year=1964)
# note that keywords are not string literals
# note the use of equals rather than colon for the assignment
print(thisdict)

Output:
{'brand': 'Ford', 'model': 'Mustang', 'year': 1964}

- @pythonpool -

⚠️ Daily Python Facts ⚠️

The math.ceil() method rounds a number upwards to its nearest integer, and the math.floor() method rounds a number downwards to its nearest integer, and returns the result

import math

x = math.ceil(1.4)
y = math.floor(1.4)

print(x) # returns 2
print(y) # returns 1

- @pythonpool -