Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
👍10👾5🆒1
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/CodeProgrammer✅
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
👍13👾2🎉1
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 #R
https://t.me/CodeProgrammer✅
Please open Telegram to view this post
VIEW IN TELEGRAM
💯13👍7🔥1🎉1
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 practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
🌟 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 practices—such as feature engineering or balancing response variables—or 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/CodeProgrammer✅
Please open Telegram to view this post
VIEW IN TELEGRAM
👍12🔥3❤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!
♻️ Repost if you found this useful
⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
- 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!
♻️ Repost if you found this useful
Please open Telegram to view this post
VIEW IN TELEGRAM
👍9❤4