....
Silhouette coefficient: A score from -1 to 1 describing the clusters found during modeling. A score near zero indicates overlapping clusters, and scores less than zero indicate data points assigned to incorrect clusters. A
Stop words: A list of words removed by natural language processing tools when building your dataset. There is no single universal list of stop words used by all-natural language processing tools.
In supervised learning, every training sample from the dataset has a corresponding label or output value associated with it. As a result, the algorithm learns to predict labels or output values.
Test dataset: The data withheld from the model during training, which is used to test how well your model will generalize to new data.
Training dataset: The data on which the model will be trained. Most of your data will be here.
Transformer: A more modern replacement for RNN/LSTMs, the transformer architecture enables training over larger datasets involving sequences of data.
In unlabeled data, you don't need to provide the model with any kind of label or solution while the model is being trained.
In unsupervised learning, there are no labels for the training data. A machine learning algorithm tries to learn the underlying patterns or distributions that govern the data.
Silhouette coefficient: A score from -1 to 1 describing the clusters found during modeling. A score near zero indicates overlapping clusters, and scores less than zero indicate data points assigned to incorrect clusters. A
Stop words: A list of words removed by natural language processing tools when building your dataset. There is no single universal list of stop words used by all-natural language processing tools.
In supervised learning, every training sample from the dataset has a corresponding label or output value associated with it. As a result, the algorithm learns to predict labels or output values.
Test dataset: The data withheld from the model during training, which is used to test how well your model will generalize to new data.
Training dataset: The data on which the model will be trained. Most of your data will be here.
Transformer: A more modern replacement for RNN/LSTMs, the transformer architecture enables training over larger datasets involving sequences of data.
In unlabeled data, you don't need to provide the model with any kind of label or solution while the model is being trained.
In unsupervised learning, there are no labels for the training data. A machine learning algorithm tries to learn the underlying patterns or distributions that govern the data.
π8
_______ A technique used to extract features from a text.
Look at details in the comment box.
Look at details in the comment box.
Anonymous Poll
47%
Data Vectorization
46%
Bag of Words
6%
None
π4
How to Use Jupyter Notebook in Amharic
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https://youtu.be/SSTkxEOlinQ
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π₯2
Tips how to write modular code for everyone
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https://youtu.be/cN0O4I6DU60
Would you please share this post?
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How to Write Modular Code | Tips to writing Modular Code
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Learn about how to write modular code. In this video, you will learn some tips how to write modular code.
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https://bit.ly/363MzLo
Learn about how to write modular code. In this video, you will learn some tips how to write modular code.
#python #machinelearning #datascience
Ask your question at https://t.me/epythonlab/β¦
π6
print(eval("2+3**2")) ?
Find resources at the comment box if you get confused
Find resources at the comment box if you get confused
Anonymous Poll
44%
2+3**2
16%
8
40%
Error
π6
Read How to Apply to Google Summer Code - GoSC
@epythonlab
https://www.freecodecamp.org/news/how-to-apply-to-google-summer-of-code/
@epythonlab
https://www.freecodecamp.org/news/how-to-apply-to-google-summer-of-code/
freeCodeCamp.org
How to Apply to Google Summer of Code β GSoC Application Guide
By Jagruti Tiwari If you have heard of Google Summer of Code but aren't sure how to apply, then read on. Whether you are a college student or a working professional, GSoC now is open to both. What is GSoC and How Does it Work? GSoC is a program
π4β€1
Do you know how you can test your code in Python using unit tests?
Anonymous Poll
26%
Yes, I know it
74%
No, I want to know it
Linux Commands Tutorial for Python Developers
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1. An overview of the linux system : https://lnkd.in/esJBbxRT
2. Linux Basic Commands: https://lnkd.in/eqis4Qmm
3. Commands working with Directories: https://lnkd.in/eZb7dBsc
4. Exercises 1: Commands working with Directories : https://lnkd.in/e2JMNghK
This tutorial is for absolute beginners. Share this post to your friends.
1. An overview of the linux system : https://lnkd.in/esJBbxRT
2. Linux Basic Commands: https://lnkd.in/eqis4Qmm
3. Commands working with Directories: https://lnkd.in/eZb7dBsc
4. Exercises 1: Commands working with Directories : https://lnkd.in/e2JMNghK
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π6
Today's Top Tipπ€πππ
βοΈLinux Basic Commands: https://lnkd.in/eqis4Qmm
βοΈCommands working with Directories: https://lnkd.in/eZb7dBsc
βοΈExercises 1: Commands working with Directories : https://lnkd.in/e2JMNghK
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βοΈLinux Basic Commands: https://lnkd.in/eqis4Qmm
βοΈCommands working with Directories: https://lnkd.in/eZb7dBsc
βοΈExercises 1: Commands working with Directories : https://lnkd.in/e2JMNghK
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Useful Linux Commands for File Manipulation
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https://www.youtube.com/watch?v=ZZIqAF1dlYM&list=PL0nX4ZoMtjYFETKxBKilFhXm_D41-5ucu&index=5
Don't forget to share and subscribe
https://www.youtube.com/watch?v=ZZIqAF1dlYM&list=PL0nX4ZoMtjYFETKxBKilFhXm_D41-5ucu&index=5
YouTube
Linux Commands for Python Developers: Commands working with files
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In this tutorial, you will learn about file manipulation linux commands. Please watch the previous videos to learn about basic commands and working with directories.
#python #linux #kalilinuxβ¦
https://bit.ly/363MzLo
In this tutorial, you will learn about file manipulation linux commands. Please watch the previous videos to learn about basic commands and working with directories.
#python #linux #kalilinuxβ¦
π₯2π1
Today's Top Tip π₯³π€
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How do you create parent directories on Linux?
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How do you create parent directories on Linux?
#linux #epythonlab
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