#R Language Data Visualization

Stop suffering in silence. These tools will level up your analysis game! Which one’s your fav? Comment down👇🏻 #dataanalysis #phdlife #statsmadeeasy #dataanalysis #rstats #prism #researchtools #scientificreels #academiaa #phd #phdwithanjali #juliusai @try_julius.ai

R vs Python: Key Differences R: - Focuses on data analysis and statistics - Used primarily by academics and researchers - Powerful data visualization with libraries like ggplot2 - Runs on the RStudio IDE - Steeper learning curve initially Python: - Versatile language used for deployment and production - Favored by programmers and developers - Strong data manipulation capabilities with pandas - Integrates with machine learning libraries like TensorFlow - Smoother, more linear learning curve Both are robust data analysis tools, but have different strengths and user bases. Choosing between R and Python depends on your specific needs and background. #DataScience #Programming #RvsPython #DataAnalysis #Statistics #AcademicResearch #Developers #MachineLearning #DataVisualization #RStudio #Python #DataManipulation

R y yo es una relación de amor / odio👩🏻‍💻 #rstudio #ranguage #rstats #bioinformatics #coding #biology #programation #humor #reels #mexico #programmer #fypシ #parati #biochemistry #scientist #womeninstem #womenwhocode #stem

A tip if you’re trying to learn R ⬇️ SWIRL is a package within R Studio that has tutorials so you can “learn R within R.” I did the R Programming course as an assignment a year or so ago and now use it to refresh my memory about basic terms and codes within R. It also looks like there are quite a few “courses” within SWIRL that are not just for beginners if you already know some R and want to advance - although I haven’t tried them yet 😄 Share this with your friends who might find this useful since R is surprisingly necessary for a lot of majors and academic fields 👩🏼‍💻 #rprogramming #collegetips #gradschool #womeninstem #r

📚 Starting a new learning journey! 🤓 For the next two months, Dive into the world of R programming language to enhance my data analysis skills. Here's what you should plan to cover: Month 1: 📌 Basics of R programming, data structures, and functions 📌 R packages and libraries for data manipulation and visualization 📚 Resources: ➡️ R Programming A-Z™ on Udemy, ➡️ R for Data Science book by Hadley Wickham and Garrett Grolemund, ➡️ DataCamp courses Month 2: 📌 Statistical analysis and modeling, machine learning algorithms 📌 Web scraping and text analysis 📌 Putting it all together with a real-world project 📚 Resources: ➡️ Introduction to Machine Learning with R book by Scott V. Burger ➡️ Web Scraping with R course on DataCamp, ➡️ Data Science Projects in R book by Prabhanjan Narayanachar Tattar . Check link in bio for free Roadmap and Resources . Are you excited to learn new things and expand my knowledge! Follow along for updates 🚀 . Follow @citizendatascientist for more related content. . Get notified right away on our daily content, tap the triple dots on the top right “…” and tap ‘Turn Post Notifications On’ . . #data #datascience #dataanalyst #dataanalysis #dataanalytics #sql #dataengineer #dataengineering #coding #coder #programming #programmer #programmerlife #coder #dataengineer #developer #100daysofcode #python #codingisfun #codinglife #programmers #datastructures r #coderslife #Python #R #DataScience #ProgrammingLanguages 🐍📊

⭐⭐📈🗣🇩🇪🇪🇸🇬🇧🇫🇷📊⭐⭐ 🗣🇺🇸: This data visualization shows which languages are most commonly learned in European countries. The data base is from a popular language learning app and refers to the year 2023. The first map shows the most popular language, the second map shows the second most popular language. 🗣🇩🇪: Diese Datenvisualisierung zeigt welche Sprachen in den Ländern Europas am häufigsten gelernt wird. Die Datengrundlage ist von einer beliebten Sprach-Lern-App und bezieht sich auf das Jahr 2023. Die erste Karte gibt dabei an, welche Sprache am häufigsten gelernt wird. Die zweite Karte zeigt die Sprache mit der zweithöchsten Präferenz. #language #skills #learning #school #english #german #french #spanish #sprache #deutsch #englisch #französisch #spanisch #lernen #datavisualization #dataanalysis #datascience #swr

My second most asked question is always how I learnt R     I taught myself mainly by just trial and error (I have to actually physically do something I can’t just watch videos as I don’t take it in) so I started with the very basics.   I think it’s so easy to overdo and feel like you need to know how to do everything or a lot of things at the start. Stick to simple things like understanding the R studio interface and loading packages and other basic commands     (after this most things I learnt were googling very specifically what I needed to do and adding the command to a ‘useful command’ list I have)    Next:  Following a vignette from start to finish (one that would be similar to what I would soon need) I then would go through and click on functions to look at the arguments (this tells you all the parameters for the function) and how I can change them if needed!    Finally try swirl it’s so easy to just load directly in the terminal and you learn as you go!        What’s your top tips?    I also have so many more so make sure you follow!      #phd #student #coding #rprogramming #university #tipsandtricks

The power of visualization in the modern age:In today’s fast-paced, information-rich world, visualization is more than just a tool—it’s a universal language that transforms complex data into meaningful knowledge, enabling clearer understanding, faster decision-making, and deeper learning across every field. Can't focus? The root cause is in your DNA—wired to wander, designed to drift. But hey, you’re not alone! 🌊 Don’t miss our latest podcast on Digital Dhiarya’s YouTube channel, where we dive into sound healing and its impact on focus. . . . @digitaldhairya @vibhushri_riveshvade #MindOnTheRun #FocusStruggles #SoundHealing #dna #healing #comfort #relaxation #GoodVibes #healthymindset #PodcastAlert #digitaldhairya

A Guide to Choose the Right Graph for Data Visualization! #datascience #datavisualization #datasciencejobs #data #dataanalysis #dataanalytics #datascientist #machinelearning #artificialintelligence #ai #machinelearningprojects #datascienceprojects #amankharwal

1️⃣ “R for Data Science” by Wickham et al. is widely recommended across stats forums as one of the best books to learn hands on R programming. The is available online for free at www.r4ds.hadley.nz 2️⃣ HarvardX Data Science R Basics is free to audit assumes no prior knowledge and teaches you foundational programming concepts and operations (it doesn’t get into statistical modeling yet). 3️⃣ “An Introduction to Statistical Learning with Applications in R” by James et al. can be a little bit more technical and advanced (as it actually covers statistical topics), but comes with great real-life R coding examples.The PDF of the book is available online for free at www.statlearning.com 4️⃣ www.rscreencasts.com has a long list of screencast videos by data scientist David Robinson where he shares real-world examples of live data analyses in R, including how to approach analysis, what packages and methods he uses, as well as general R tricks and tips. 5️⃣ If you prefer more interactive learning, you might enjoy swirl (swirlstats.com) that teaches you R programming interactively inside the R console, no reading books or watching courses required. ❓Any other good recs? Drop them in the comments! #rprogramming #rstudio #datascientist #womenintech #womeninstem

🔥 I spent 2 weeks simplifying RAG. Here’s the clearest breakdown you’ll ever see .. RAG turns a general LLM into a domain expert using your knowledge. 💡  What is RAG ? Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response. RAG has 3 major steps: 1️⃣  Retrieve: Find relevant information from your own data using embeddings + vector search. 2️⃣  Augment: Inject the retrieved chunks into the LLM prompt as context. This step ensures the model has the exact information it must use. This step prevents hallucination. 3️⃣  Generate: The LLM produces the final answer using both, The user’s question and the retrieved context 🌟 Why RAG Is a Big Thing Right Now 1. No fine-tuning needed - You can use your custom data instantly 2. Reduces hallucination - AI answers are grounded in facts 3. Super scalable - Works with millions of documents 4. Cheaper than training models - Retrieval minimizes token usage 5. Perfect for enterprise - Safe, controllable, auditable 6. Best way to build AI apps - Chatbots, copilots, search engines, document bots Follow @navokitech for more posts #explorepage #foryoupage #trendingreels #fyp #infographics #agenticai #rag #explore #navoki #softwareengineer #mobileappdevelopment #peoplewhocode #coding #computerscience #100daysofcode #programming #programmerslife💻  #webdeveloper #aicreator #generativeai #artificialintelligence #datascience

Dive into the mind of AI! Data scientist Santiago Ortiz has crafted a fascinating project that visualizes how large language models, like ChatGPT, "think." By repeatedly generating the phrase "Intelligence is" hundreds of times, the project uncovers how these models connect and expand on ideas. This captivating visualization breaks down complex patterns, making the inner workings of advanced AI more accessible to everyone. Explore it here: https://moebio.com/mind/ #ai #artificialintelligence #tech #chatgpt #innovation #future #ainews #trending #viral