555.4K
CHThe best projects serve a real use case
Comment “data” for all the links and project descriptions
#tech #data #datascience #ml #explore
@chrisoh.zip
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WOSteve brunton is sooo GOATEDDD !!!
#machinelearning #datascience #stem #artificialintelligence
@workiniterations
1.3M
IBJunior vs Senior: A python program that removes duplicate elements from a list while keeping the original order. #python #learnpython #programming
#datascience #pythonprogramming
@ibrahimmanarbkh
252.1K
KRThe Ultimate Pathfinding Algorithm Race is HERE! 🚀🏁 Who will find the perfect path first?
Watch A*, Dijkstra, BFS, DFS, Greedy, Bi-BFS, and Prim go head-to-head in this stunning coding visualization. 💻 Wait until the end to see which one expands the nodes fastest and finds the most optimal route!
1️⃣ Dijkstra - reliable but exhaustive
2️⃣ A* (A-Star) - the smart heuristic speedster
3️⃣ Greedy - fast but risky
4️⃣ Bi-BFS - meeting halfway! 🤯
5️⃣ BFS - slow and steady
6️⃣ DFS - diving into dead ends
7️⃣ Prim - the spanning tree master
Which one is your go-to in coding interviews? Let me know in the comments! 👇
Don't forget to LIKE and FOLLOW for more satisfying and educational algorithm visualizations! 🌟
#algorithmrace #programming #computerscience #tech #dijkstra #astar #pathfinding #softwareengineering #datastructures #codinglife #webdev #datascience
@kreggscode
1.8M
SHConfused between becoming a Data Scientist or an AI Engineer?
Both roles are powerful—but require different skills, tools, and thinking.
Comment “Roles” and I’ll send you a detailed roadmap for both 🚀
Got questions or feeling stuck? Drop your doubts in the comments—I’ll personally help you get clarity and move forward on your journey.
#datascientist #datascience #ai #aiengineer #careergrowth
@shailjamishra__
366.0K
DAHere are 3 unique data science projects you can build in a weekend (2026 World Cup)
easy. a World Cup match outcome predictor. predict win, loss, or draw using historical FIFA data. tech stack: Python, Pandas, Scikit-learn, and Streamlit to deploy it.
medium. a player performance dashboard. pull player stats from Transfermarkt, visualize everything, and cluster players by playing style. tech stack: Python, Pandas, Plotly, and Seaborn for visualization with KMeans for clustering.
hard. a real time World Cup sentiment tracker. pull live tweets during matches, run sentiment analysis as goals happen, and visualize how public opinion shifts in real time. tech stack: Python, Tweepy for the Twitter API, HuggingFace Transformers for sentiment analysis, and Plotly Dash for the live dashboard.
comment “World cup” for resources to help you out along the way.
#machinelearning #datascience #ai #python #cs
@darshcoded
357.8K
VOData Science Trivia | Did you get the last one? #datascience #dataanalytics #datascientist #math #finance
@voodiesinterviews
275.1K
THcomment “learn” and I will DM you the links 🔗
#softwareengineer #ai #machinelearning #datascience #swe
@thad.codes
241.3K
QUReality vs Expectation, there’s a reason why there’s a divergence.
Many of the “standard” models have inherent flaws that fail to embed sufficient information. This problem propagates across most standard models from the standard use of “distributions” to “markov chain Monte Carlo” to the “standard volatility modeling approaches”, and the problem isn’t that they assume single regimes or that they assume vol is constant…
They certainly work as they’re supposed to, they just fail to capture a lot of important information.
📣 to dive deeper into the methodology and how you can replicate this, see the link in my bio
#quant #ai #quantfinance #datascience #trading
@quant_research_decoded
1.4M
MAclass was not my line of best fit #datascience #ucberkeley #student #cs
@masahkikhia
407.7K
CLFollow @cloud_x_berry for more info
#TechSalary #ITJobs #CareerGrowth #SoftwareEngineer #DataScience
fresher salary india, 3 years experience salary, 5 years experience salary, software developer salary india, full stack developer salary, backend developer salary, frontend developer salary, data analyst salary india, data scientist salary india, machine learning engineer salary, cloud engineer salary india, devops engineer salary, cyber security salary india, qa tester salary india, ui ux designer salary india, business analyst salary india, product manager salary india, project manager salary india, tech career growth india, highest paying IT jobs
@cloud_x_berry
1.7M
SHLists are one of the most frequently used data structures in Python. Whether you’re cleaning data, transforming records, or building quick scripts for analysis, understanding list methods can significantly improve your efficiency.
Here’s what makes them powerful:
• Adding elements dynamically when new data arrives
• Counting occurrences to validate patterns
• Copying lists safely before transformations
• Locating positions of specific values
• Inserting elements at precise indexes
• Reversing sequences for logical operations
• Removing items selectively
• Clearing data structures when resetting workflows
In real-world analytics, these small operations save time, reduce bugs, and keep your code clean.
If you work with Python for data analysis, automation, scripting, or interviews, list methods are foundational. They appear simple, but they control how your data flows.
Save this for revision and quick recall before interviews or while practicing.
[python, pythonlists, listmethods, pythonforanalysis, dataanalysis, datascience, coding, programming, pythonlearning, pythonbasics, pythoninterview, analystskills, datastructures, codingpractice, techskills, analytics, automation, softwaredevelopment, pythondeveloper, learnpython, pythoncode, datacleaning, eda, scripting, developerlife, techcareer, programmingtips, pythoneducation, pythoncommunity, ai, machinelearning, businessanalytics, techgrowth, careerintech, dataengineering, dataanalyticslife, pythonprojects, codingjourney, learncoding, analyticscareer, developercommunity, pythontraining, interviewprep, dataprocessing, techcontent, pythonresources, programminglife, coderlife, pythonpractice, techlearning]
#Python #DataAnalytics #Programming #DataScience #TechCareer
@she_explores_data
✨ #Datascience Discovery Guide
Instagram hosts 3 million posts under #Datascience, creating one of the platform's most vibrant visual ecosystems. This massive collection represents trending moments, creative expressions, and global conversations happening right now.
The massive #Datascience collection on Instagram features today's most engaging videos. Content from @shailjamishra__, @she_explores_data and @masahkikhia and other creative producers has reached 3 million posts globally. Filter and watch the freshest #Datascience reels instantly.
What's trending in #Datascience? The most watched Reels videos and viral content are featured above. Explore the gallery to discover creative storytelling, popular moments, and content that's capturing millions of views worldwide.
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💡 Top performing posts average 1.5M views (1.9x above average). Moderate competition - consistent posting builds momentum.
Post consistently 3-5 times/week at times when your audience is most active
Content Creation Tips & Strategy
💡 Top performing content gets over 10K views - focus on engaging first 3 seconds
📹 High-quality vertical videos (9:16) perform best for #Datascience - use good lighting and clear audio
✨ Many verified creators are active (33%) - study their content style for inspiration
✍️ Detailed captions with story work well - average caption length is 496 characters
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