#data science project

[reasonsforhope]

If you're feeling anxious or depressed about the climate and want to do something to help right now, from your bed, for free...

Start helping with citizen science projects

What's a citizen science project? Basically, it's crowdsourced science. In this case, crowdsourced climate science, that you can help with!

You don't need qualifications or any training besides the slideshow at the start of a project. There are a lot of things that humans can do way better than machines can, even with only minimal training, that are vital to science - especially digitizing records and building searchable databases

Like labeling trees in aerial photos so that scientists have better datasets to use for restoration.

Or counting cells in fossilized plants to track the impacts of climate change.

Or digitizing old atmospheric data to help scientists track the warming effects of El Niño.

Or counting penguins to help scientists better protect them.

Those are all on one of the most prominent citizen science platforms, called Zooniverse, but there are a ton of others, too.

Oh, and btw, you don't have to worry about messing up, because several people see each image. Studies show that if you pool the opinions of however many regular people (different by field), it matches the accuracy rate of a trained scientist in the field.

--

I spent a lot of time doing this when I was really badly injured and housebound, and it was so good for me to be able to HELP and DO SOMETHING, even when I was in too much pain to leave my bed. So if you are chronically ill/disabled/for whatever reason can't participate or volunteer for things in person, I highly highly recommend.

Next time you wish you could do something - anything - to help

Remember that actually, you can. And help with some science.

[millenniallust4death]

I’ve posted about it before, but I’ve been working on archiving Martin and Bosco’s blaze post in case Tumblr randomly disappears one day like a cartoon on HBO Max. I figured I’m probably not the only person or community who wants to archive their Tumblr posts, so I made a project website to explain what I’m doing. It all feels ridiculously extra, but that’s how I am about data science stuff.

You’re welcome to follow along with the project if you’re interested in the post or want to learn a bit about how to make sense of data. Questions are always welcome — whether you're curious about the methods, confused by the plots, wondering what’s next, or just thinking, “can I archive my own posts?”.

Link to the project website: https://lebriggs.com/ Note: The website is readable on mobile, but dashboards aren't really built for enjoyable small screen viewing.

Here’s a screenshot of a dashboard to get your started — you can find it on the website in an interactive form.

[idol--hands]

Star Trek Annual [2024, pt.1/3]

Months ago, Emperor Kahless attempted to exterminate the many species across the galaxy who call themselves “gods”. He allied with the brilliant Klingon scientist Korath, who built him the “godkiller array” using the long-lost Bajoran Orb of Destruction as its energy source. . But when Kahless attempted to utilize that energy to consolidate power on his own people during the Day of Blood, he was stopped by the combined efforts of two Starfleet vessels: the U.S.S. Theseus and the U.S.S. Defiant. . Korath, however, escaped justice when he and the now-shattered Orb of Destruction were kidnapped by the Defiant’s science officer: the rouge android known only as Lore. For months, Data has searched the galaxy for any sings of Lore. No clue to his plans has been discovered. . His trail has gone cold…

[itsahotminuteinbetween]

Venting on the Internet:

I know this is probably only going to get a couple of notes but I need as MUCH data as possible so PLEASE VOTE AND REBLOG!

[silvergreenseraphim]

Hmm, I am looking through endless Ultimania translations to find a bit of information on a Crisis Core scene that will help me finish a post but as usual I became distracted.

(From the Crisis Core guide).

I was thinking about this fusion pod that Hojo lets Zack enter. Hojo can also apparently use it to physically enhance subjects?

Somehow Zack is infused to become stronger and then….

Hmmm.

Too much enhancement leads to degradation for SOLDIERs.

Alas, they all have their limits.

Well. Except one…

“You do not have the ability to copy unto others. Your DNA cannot be spread. Thus your body cannot deteriorate.”

Sephiroth’s cells have no limitations. How proud Hojo must have been, to discover that his first-rate science experiment, could not degrade or reach the limit of his cells.

He could enhance Sephiroth endlessly, making him stronger and stronger. Always superior to Hollander’s experiments. Never reaching a limit to what Project S could endure.

There was no threshold, was there?

[atlaskrr]

I NEED SURVEY RESPONSES

hey guyssssssssssssssssssssss. i have a school project and the data just aint it. please help by filling it in and spreading it by rbing or whatever tyyyyy

[creativeronica]

I'm creating designs that stand against tyranny. This specific design will show that you protest the fascist takeover of the United States of America. RESIST. RESIST. RESIST. NEVER RELENT. The fascists won't.

[bunnyboy-juice]

WAWAWAWAWAWAWAWA

[everydaydeeds]

Day 4072 - Happy Citizen/Community Science Month! And Earth Month! I did a FeederWatch count today and got caught up on my last few weeks of data entry.

[uditprajapati7685]

Pickl.AI offers a comprehensive approach to data science education through real-world case studies and practical projects. By working on industry-specific challenges, learners gain exposure to how data analysis, machine learning, and artificial intelligence are applied to solve business problems. The hands-on learning approach helps build technical expertise while developing critical thinking and problem-solving abilities. Pickl.AI’s programs are designed to prepare individuals for successful careers in the evolving data-driven job market, providing both theoretical knowledge and valuable project experience.

[millenniallust4death]

Recall: My original goal was to write R code to back up my Blaze post in case Tumblr disappears.

Here’s what I learned about Tumblr’s rickety API based on a test post with ~800 notes.

What I thought I would see:

A beautiful reblog tree, clearly showing how my post spread across Tumblr — every reblog linked to the one it came from.

Posts with tags would show up as blue dots in my version tree. (Tags interest me because they represent people who more deeply engaged with my post. And I'm nosy. XD)

What Tumblr’s rickety API actually gave me:

Orphaned nodes. Reblogs that definitely happened but aren’t connected to anything.

I expected to get a clean version history: Original Post (Blog A) → Blog B → Blog C

But the API fucker just shrugs and tells you C reblogged A. What the fuck happened to Blog B?

The result is that whole branches of the tree vanish. And that’s in addition to the reblogs that are missing because of the API respecting blog privacy settings (as it definitely should).

Conclusion:

As always, I feel disappointed but not surprised by Tumblr’s inability to fully function. The data doesn’t reflect what I know Tumblr users actually did; it just reflects what the API is willing to share.

I am so tired.

TL;DR: Nope. I cannot fully back up my Blaze post using the rickety API.

A quick rendering of the reblog version tree from the test post — a visual representation of my disappointment.

[sonadukane]

How to Become a Data Scientist in 2025 (Roadmap for Absolute Beginners)

Want to become a data scientist in 2025 but don’t know where to start? You’re not alone. With job roles, tech stacks, and buzzwords changing rapidly, it’s easy to feel lost.

But here’s the good news: you don’t need a PhD or years of coding experience to get started. You just need the right roadmap.

Let’s break down the beginner-friendly path to becoming a data scientist in 2025.

✈️ Step 1: Get Comfortable with Python

Python is the most beginner-friendly programming language in data science.

What to learn:

Variables, loops, functions

Libraries like NumPy, Pandas, and Matplotlib

Why: It’s the backbone of everything you’ll do in data analysis and machine learning.

🔢 Step 2: Learn Basic Math & Stats

You don’t need to be a math genius. But you do need to understand:

Descriptive statistics

Probability

Linear algebra basics

Hypothesis testing

These concepts help you interpret data and build reliable models.

📊 Step 3: Master Data Handling

You’ll spend 70% of your time cleaning and preparing data.

Skills to focus on:

Working with CSV/Excel files

Cleaning missing data

Data transformation with Pandas

Visualizing data with Seaborn/Matplotlib

This is the “real work” most data scientists do daily.

🧬 Step 4: Learn Machine Learning (ML)

Once you’re solid with data handling, dive into ML.

Start with:

Supervised learning (Linear Regression, Decision Trees, KNN)

Unsupervised learning (Clustering)

Model evaluation metrics (accuracy, recall, precision)

Toolkits: Scikit-learn, XGBoost

🚀 Step 5: Work on Real Projects

Projects are what make your resume pop.

Try solving:

Customer churn

Sales forecasting

Sentiment analysis

Fraud detection

Pro tip: Document everything on GitHub and write blogs about your process.

✏️ Step 6: Learn SQL and Databases

Data lives in databases. Knowing how to query it with SQL is a must-have skill.

Focus on:

SELECT, JOIN, GROUP BY

Creating and updating tables

Writing nested queries

🌍 Step 7: Understand the Business Side

Data science isn’t just tech. You need to translate insights into decisions.

Learn to:

Tell stories with data (data storytelling)

Build dashboards with tools like Power BI or Tableau

Align your analysis with business goals

🎥 Want a Structured Way to Learn All This?

Instead of guessing what to learn next, check out Intellipaat’s full Data Science course on YouTube. It covers Python, ML, real projects, and everything you need to build job-ready skills.

https://www.youtube.com/watch?v=rxNDw68XcE4

🔄 Final Thoughts

Becoming a data scientist in 2025 is 100% possible — even for beginners. All you need is consistency, a good learning path, and a little curiosity.

Start simple. Build as you go. And let your projects speak louder than your resume.

Drop a comment if you’re starting your journey. And don’t forget to check out the free Intellipaat course to speed up your progress!

[delicatelysublimeforester]

Seeing Red: Colorfully Attired Organisms in the City Nature Challenge!

[d0nutzgg]

Tonight I am hunting down venomous and nonvenomous snake pictures that are under the creative commons of specific breeds in order to create one of the most advanced, in depth datasets of different venomous and nonvenomous snakes as well as a test set that will include snakes from both sides of all species. I love snakes a lot and really, all reptiles. It is definitely tedious work, as I have to make sure each picture is cleared before I can use it (ethically), but I am making a lot of progress! I have species such as the King Cobra, Inland Taipan, and Eyelash Pit Viper among just a few! Wikimedia Commons has been a huge help!

I'm super excited.

Hope your nights are going good. I am still not feeling good but jamming + virtual snake hunting is keeping me busy!

[the-awesomecosmos-studies]

Feb 19, 2024

Day 1 of 100 days of productivity. Went to a local cafe, worked on the data cleaning for my side project in RStudio, got an iced coffee and poppyseed cake slice. Sent some emails, polished an old blog article and posted it. 7/10 productive vibes today.