#ICYMI An Overview of #Python #DeepLearning Frameworks http://buff.ly/2mdtdY3
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Working With Numpy Matrices: A Handy First Reference http://buff.ly/2m8XgQ8 #Python #Analytics #MachineLearning
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How to Solve a Staff Scheduling Problem with Python
https://towardsdatascience.com/how-to-solve-a-staff-scheduling-problem-with-python-63ae50435ba4
#Python #DS
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https://towardsdatascience.com/how-to-solve-a-staff-scheduling-problem-with-python-63ae50435ba4
#Python #DS
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Medium
How to Solve a Staff Scheduling Problem with Python
Minimize the number of workers per shift while assigning enough workers for each time window
An overview of the fundamental data science/AI libraries:
• numpy is the quintessential library for scientific computing in Python, in that in supports high-performance arithmetic in batches via its array data structure.
• pandas builds on numpy in that it supports SQL-style manipulation of tabular data.
Numpy and pandas encourage you to conceptualize your data as "one thing". Unlike the rest of Python, writing "explicit" for loops for numpy and pandas operations is actually less communicative than using the provided functions and methods (which are optimized), and should be avoided as much as possible.
• sklearn has general-purpose machine learning tools as well as ready-made implementations of popular algorithms that you can fit to your data.
• scipy implements functions that are useful for scientific computing that aren't found in numpy.
• matplotlib is used for data visualization.
• PyTorch and Tensorflow are both used for deep learning that can benefit from GPU computation.
#python #libraries #DS #AI #ML #DL
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• numpy is the quintessential library for scientific computing in Python, in that in supports high-performance arithmetic in batches via its array data structure.
• pandas builds on numpy in that it supports SQL-style manipulation of tabular data.
Numpy and pandas encourage you to conceptualize your data as "one thing". Unlike the rest of Python, writing "explicit" for loops for numpy and pandas operations is actually less communicative than using the provided functions and methods (which are optimized), and should be avoided as much as possible.
• sklearn has general-purpose machine learning tools as well as ready-made implementations of popular algorithms that you can fit to your data.
• scipy implements functions that are useful for scientific computing that aren't found in numpy.
• matplotlib is used for data visualization.
• PyTorch and Tensorflow are both used for deep learning that can benefit from GPU computation.
#python #libraries #DS #AI #ML #DL
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Netflix Movies and TV Shows Analysis.pdf
738.8 KB
Netflix Movies and TV Shows Analysis (Python Implementation)
1. Importing Libraries and Dataset
2. Data Cleaning and Preprocessing
3. Data Visualization
#python #datavisualization #netflix #python3 #pythonprogramming #pythonprogramminglanguage #datascience
Credit: Nirmal Gaud
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1. Importing Libraries and Dataset
2. Data Cleaning and Preprocessing
3. Data Visualization
#python #datavisualization #netflix #python3 #pythonprogramming #pythonprogramminglanguage #datascience
Credit: Nirmal Gaud
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Harvard CS109A #DataScience course materials — huge collection free & open!
1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
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1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
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Pornhub Explanatory Data Analysis.pdf
1.4 MB
Pornhub - Exploratory Data Analysis (Python Implementation)
1. Loading the libraries
2. Loading the data
3. Some preprocessing
4. Most viewed videos
5. Most viewed categories
6. Most voted categories
7. Length of video vs Number of views
8. Quality of video vs Number of views
9. Length of video vs Voting of video
10. Quality of video vs Voting of video
12. Most used words in Tags
13. Most used words in Categories
14. Most used words in Titles
#dataanalysis #data #quality #video #dataanalysis #dataanalytics #datascientist #datasciencetraining #datascience #exploratorydataanalysis #pornhub #python #pythonprogramming #pythonfordatascience #pythonprogramminglanguage
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1. Loading the libraries
2. Loading the data
3. Some preprocessing
4. Most viewed videos
5. Most viewed categories
6. Most voted categories
7. Length of video vs Number of views
8. Quality of video vs Number of views
9. Length of video vs Voting of video
10. Quality of video vs Voting of video
12. Most used words in Tags
13. Most used words in Categories
14. Most used words in Titles
#dataanalysis #data #quality #video #dataanalysis #dataanalytics #datascientist #datasciencetraining #datascience #exploratorydataanalysis #pornhub #python #pythonprogramming #pythonfordatascience #pythonprogramminglanguage
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