ChatGPT Cheat Sheet for Business - DataCamp

Unlock the full potential of AI with our comprehensive ChatGPT Cheat Sheet for Business! Tailored specifically for professionals and entrepreneurs, this guide offers actionable insights on leveraging ChatGPT to streamline workflows, enhance customer interactions, and drive business growth. Whether you're a marketing specialist, project manager, or CEO, this cheat sheet is your go-to resource for mastering conversational AI.

From crafting compelling content to automating routine tasks, learn how to harness the power of ChatGPT in real-world business scenarios. With clear examples and step-by-step instructions, you’ll be able to integrate ChatGPT seamlessly into your operations, improving efficiency and innovation.

Don’t miss out on staying ahead of the competition by embracing the future of AI-driven solutions!

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Top 100 Machine Learning Interview Questions & Answers Cheatsheet

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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

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Master PyTorch Faster with These Free Resources!
Whether you're just getting started with PyTorch or looking to refresh your deep learning skills, these two resources are all you need:

1. PyTorch Cheatsheet
A concise reference guide packed with essential PyTorch commands and patterns. Perfect for quick look-ups during development.
Download:
https://www.dropbox.com/scl/fi/e4xngykrfoubiw3xnd6fz/PyTorch-Cheatsheet.pdf?rlkey=vgx38ckps7aie120imgozgq4g&e=2&st=hgs06d4t&dl=0

2. Learn PyTorch Deep Learning with Hands-On Code
A beginner-friendly PDF with practical examples to help you build and train deep learning models using PyTorch from scratch.
Download:
https://www.dropbox.com/scl/fi/lfo7r6fnd8wjm3gp0jteh/Learn-PyTorch-Deep-Learning-with-Hands-On-Code.pdf?rlkey=mg9cxg41yerouzp0rklm8hqa2&e=2&st=c7k7rgay&dl=0

Save them, share them, and start building smarter models today!

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⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟

Unlock the full power of SciPy with my comprehensive cheat sheet!
Master essential functions for:

Function optimization and solving equations

Linear algebra operations

ODE integration and statistical analysis

Signal processing and spatial data manipulation

Data clustering and distance computation ...and much more!

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💯 BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟

🔥 Huge cheat sheet for plotting in Matplotlib with code examples

📊 Matplotlib is a powerful plotting library in Python used for creating static, animated, and interactive visualizations.

Main features of Matplotlib:
💬 Versatility: can generate a wide range of plots including line plots, scatter plots, bar charts, histograms, and pie charts.

💬 Customization: offers extensive options to control every aspect of the plot such as line styles, colors, markers, labels, and annotations.

💬 Integration with NumPy: easily integrates with NumPy, simplifying plotting of data arrays directly.

💬 Publication quality: creates high-quality plots suitable for publication, with precise control over aesthetics.

💬 Extensibility: easily extended with a large ecosystem of additional toolkits and extensions, such as Seaborn and Pandas plotting functions.

💬 Cross-platform: platform-independent and can run on various operating systems including Windows, macOS, and Linux.

💬 Interactive plots: supports interactive plotting with widgets and event handling, allowing users to dynamically explore data.

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Matplotlib Cheatsheet (⭐️⭐️⭐️⭐️⭐️)

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