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π11β€3π―1
Machine Learning Algorithm basics!
Support Vector Machines (SVM) vs k-Nearest Neighbors (k-NN)
#MachineLearning #algorithms #ML #DataScience #ArtificialIntelligence #AI
https://t.me/CodeProgrammerπ
Support Vector Machines (SVM) vs k-Nearest Neighbors (k-NN)
#MachineLearning #algorithms #ML #DataScience #ArtificialIntelligence #AI
https://t.me/CodeProgrammer
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π8
The popular free LLM course has just been updated.
This is a step-by-step guide with useful resources and notebooks for both beginners and those who already have an ml-base.
The course is divided into 3 parts:
#llm #course #opensource #ml
https://t.me/CodeProgrammer
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π13β€2
Fetch Trending Searches using Python π₯
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
https://t.me/CodeProgrammerπ
#python #programming #developer #programmer #coding #coder #softwaredeveloper #computerscience #webdev #webdeveloper #webdevelopment #pythonprogramming #pythonquiz #ai #ml #machinelearning #datascience
https://t.me/CodeProgrammer
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π10β€1π―1
Best Data Analyst Online Certifications!
https://www.mltut.com/data-analyst-online-certification-to-become-a-successful-data-analyst/
#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics
https://t.me/CodeProgrammerβοΈ
https://www.mltut.com/data-analyst-online-certification-to-become-a-successful-data-analyst/
#MachineLearning #DeepLearning #BigData #Datascience #ML #HealthTech #DataVisualization #ArtificialInteligence #SoftwareEngineering #GenAI #deeplearning #ChatGPT #OpenAI #python #AI #keras #SQL #Statistics
https://t.me/CodeProgrammer
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π9
The Hundred-Page Language Models Book
Read it:
https://github.com/aburkov/theLMbook
Read it:
https://github.com/aburkov/theLMbook
#LLM #NLP #ML #AI #PYTHON #PYTORCH
https://t.me/DataScienceM
π7
Generative AI for beginners by Microsoft
21 Lessons teaching everything you need to know to start building Generative AI applications
Enroll Free: https://github.com/microsoft/generative-ai-for-beginners
21 Lessons teaching everything you need to know to start building Generative AI applications
Enroll Free: https://github.com/microsoft/generative-ai-for-beginners
#GenerativeAI #LLM #GAN #PYTHON #PYTORCH #ML #DEEPLEARNING #RAG
https://t.me/CodeProgrammer
π13β€4π₯2
Pen and Paper Exercises in MachineLearning
Free 211-page PDF: arxiv.org/abs/2206.13446
GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises
Free 211-page PDF: arxiv.org/abs/2206.13446
GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises
#DataScientist #AI #ML #DataScience #LLM #PYTHON #PYTORCH #DEEPLEARNING #GenerativeAI
https://t.me/CodeProgrammer
π15β€5
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π Cheat sheets for data science and machine learning
Link: https://sites.google.com/view/datascience-cheat-sheets
Link: https://sites.google.com/view/datascience-cheat-sheets
#DataScience #MachineLearning #CheatSheet #stats #analytics #ML #IA #AI #programming #code #rstats #python #deeplearning #DL #CNN
https://t.me/CodeProgrammerβ
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π19β€11
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π10πΎ5π1
Deep Learning with Keras :: Cheat sheet
#DataScience #MachineLearning #CheatSheet #stats #analytics #ML #IA #AI #programming #code #rstats #python #deeplearning #DL #CNN #Keras #R
https://t.me/CodeProgrammerβ
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π13πΎ2π1
Top_100_Machine_Learning_Interview_Questions_Answers_Cheatshee.pdf
5.8 MB
Top 100 Machine Learning Interview Questions & Answers Cheatsheet
#DataScience #MachineLearning #CheatSheet #stats #analytics #ML #IA #AI #programming #code #rstats #python #deeplearning #DL #CNN #Keras #Rο»Ώ
https://t.me/CodeProgrammerβ
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π―13π7π₯1π1
Machine Learning from Scratch by Danny Friedman
This book is for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different algorithms create the models they do and the advantages and disadvantages of each one.
This book will be most helpful for those with practice in basic modeling. It does not review best practicesβsuch as feature engineering or balancing response variablesβor discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
π Link: https://dafriedman97.github.io/mlbook/content/introduction.html
This book is for readers looking to learn new machine learning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different algorithms create the models they do and the advantages and disadvantages of each one.
This book will be most helpful for those with practice in basic modeling. It does not review best practicesβsuch as feature engineering or balancing response variablesβor discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
#DataScience #MachineLearning #CheatSheet #stats #analytics #ML #IA #AI #programming #code #rstats #python #deeplearning #DL #CNN #Keras #R
https://t.me/CodeProgrammerβ
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π12π₯3β€2
ML Tools GRadio.pdf
203.3 KB
Gradio: The easiest way to demo your models.
- Core Idea: Quickly turn #ML models into interactive web apps.
- No frontend skills needed. It's all #Python.
- Works with any Python code, including custom functions.
- Share via temporary links or deploy on #HuggingFace Spaces.
- Get user feedback to improve your models.
If you're looking to create interactive demos for your ML project, check out #Gradio!
β»οΈ Repost if you found this useful
β‘οΈ BEST DATA SCIENCE CHANNELS ON TELEGRAM π
- Core Idea: Quickly turn #ML models into interactive web apps.
- No frontend skills needed. It's all #Python.
- Works with any Python code, including custom functions.
- Share via temporary links or deploy on #HuggingFace Spaces.
- Get user feedback to improve your models.
If you're looking to create interactive demos for your ML project, check out #Gradio!
β»οΈ Repost if you found this useful
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π9β€4