Davi Diniz

[Ivanildo Terceiro 🔸🌐 @ivanildoiii]

É só ir no debate responder.

[Davi Diniz @DCDMelo]

The wait for a unified Brazilian rainfall database is over. UNIPLU-BR brings together 2.2 billion records from 21k+ stations, spanning 140 years of climate history (1885–2025).
​A must-have for hydrologists, meteorologists etc.
​Check it out: https://t.co/68JcWiq36z

[Davi Diniz @DCDMelo]

@aguedescartoon Achava que era só eu que tinha esse sonho (ou seria um pesadelo?) esquisito kkk

[Davi Diniz @DCDMelo]

@RodolfoNobrega What the heck do you have in that docx? Didn't I tell you to stop saving IPCC's netcdf outputs as word files.

[Davi Diniz @DCDMelo]

Unbelievable 🤯.

[James Lindsay, anti-Communist @ConceptualJames]

The quality crisis in academia, especially in DEI-related fields, needs all the attention we can give it. It's time to fully expose the fraud in our academic centers.

[guilherme iamarino @Guiamarino]

Aniversário do professor Tolkien hoje!

Faria 132 anos se fosse vivo!

[Physics In History @PhysInHistory]

Leonardo da Vinci's anatomical sketches are masterful pieces of art.

[H-CEL Ghent @HCEL_Ghent]

On the devastating 2019–2022 drought in South America. An enlightening new study led by @joao_geirinhas
https://t.co/Ivqal4NczO).

[Rodolfo Nóbrega | @rodolfonobrega.bsky.social @RodolfoNobrega]

Very detailed article. Worth reading. #MDPIgate

[Jaydeep @_jaydeepkarale]

I've been writing about Python, Machine Learning & Data Science on Twitter for over a year now !!!

Here are some of my best posts covering
~ Tutorials
~ YT Videos
~ Certifications

& More 💪

[Reed Maxwell @reedh2o]

We are excited to announce a new publication on our ParFlow-CONUS2 model! A team effort led by @CUG_Chen and @dantetijerina with @hoang_h2o, this represents years of collaboration with @LCofthedesert’s group. [1/n]
https://t.co/Cr7R2JdFGJ

[Davi Diniz @DCDMelo]

What a incredible week @cna_hydro and I had here in @ucdavis. Thanks @KSuvocarev for hosting us and introducing us to your awesome team. We learned so much about micrometeorology & surface renewal method. Can't wait to return.

[Santiago @svpino]

To start with Machine Learning:

1. Learn Python
2. Practice using Google Colab

Take these 2 free courses:

• Introduction to Python Programming (Udacity)
• Machine Learning Crash Course (Google)

If you need a bit more time before diving deeper, finish the following Kaggle tutorials:

• Intro to Machine Learning
• Intermediate Machine Learning

At this point, you are ready to finish your first project: The Titanic Challenge on Kaggle.

If Math is not your strong suit, don't worry. I don't recommend you spend too much time learning Math before writing code. Instead, learn the concepts on-demand: Find what you need when needed.

From here, take the Machine Learning specialization in Coursera. It's more advanced, and it will stretch you out a bit.

The top universities worldwide have published their Machine Learning and Deep Learning classes online. Here are some of them:

• MIT 6.S191 Introduction to Deep Learning
• DS-GA 1008 Deep Learning
• UC Berkeley Full Stack Deep Learning
• UC Berkeley CS 182 Deep Learning
• Cornell Tech CS 5787 Applied Machine Learning

Many different books will help you. The attached image will give you an idea of my favorite ones.

Finally, keep these three ideas in mind:

1. Start by working on solved problems so you can find help whenever you get stuck.

2. ChatGPT will help you make progress. Use it to summarize complex concepts and generate questions you can answer to practice.

3. Find a community here on 𝕏 and share your work. Ask questions, and help others.

During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.

Here are the good news:

Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in the space.

Focus on finding your path, and Write. More. Code.

That's how you win.

[Aakash Kanojiya @Kanojiyaaakash1]

Google is offering free online courses with certification.

1. Applied Data Science with Python
https://t.co/UcwUq0Sfxg

2. Fundamentals of Digital Marketing
https://t.co/DAlj1s2Lak

3. Google Analytics Certification
https://t.co/NcOcBGfO5l

4. Google Ads Search Certification
https://t.co/E9tZvbtOL1

5. Google Ads Display Certification
https://t.co/uLIeEpEA7b

6. YouTube Music Certification
https://t.co/gEgFnMcW2B

7. Get started with Google Maps Platform
https://t.co/Mvomc6tGY5

8. Build apps with Flutter
https://t.co/FWfsWyCFpe

9. Introduction to SQL
https://t.co/kPPoFX9Wpp

10. Generative AI [Mega Course]
https://t.co/uKCsfEx5C7

Follow @Kanojiyaaakash1 for such free resources.

[Michael Pyrcz🌻 @GeostatsGuy]

I share all my university #educational content for any interested to learn about #DataAnalytics, #geostatistics & #MachineLearning.

Learn more about all my shared content @ https://t.co/ikPlw8Ro03. So many recorded lectures, #Python interactive demonstrations & well-documented workflows!

[SAROJ PARAJULI @Parajulisaroj16]

Nonlinear time series analysis is a powerful tool for uncovering hidden patterns and relationships within time-dependent data.  https://t.co/rpgaVTU5eh
#DataScience #rstats #Datavisualization #MachineLearning #DataAnalytics #Statistics #programming

[Davi Diniz @DCDMelo]

@74Mfilho Pois é kkkk

[Qiusheng Wu @giswqs]

All the code examples for the book are available here 👇
GitHub: https://t.co/PPr8aiFBsa
Website: https://t.co/UMC2RbSfu2

[Davi Diniz @DCDMelo]

@giswqs @locatepress Great initiative! Thanks for your contribution to this field.

[Zhongbo Kang @ZhongboK]

Apparently “The Feynman Lectures on Physics” are now completely online. Read it here: https://t.co/tpYAiB6g6b