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Data scientist | Aspiring Professor | Python & R

[. @stephen_khalaf]

@raycrypto_1 El khalaf is interested... reply immediately!

[HolisticHealthHQ @HolisticHHQ]

How to clear the fat under your chin

[Sofia khatun @sofia3973]

12 Websites that pay you daily💸💸

1. arise. com

2. kellyconnect. com

3. gaggle. net

4. paidwork. com

5. toptal. com

6. transcriptionhub. com

7. preply. com

8. omniinteractions. com

9. rev. com

10. taskrabbit. com

11. swagbucks. com

12. nexrep. com

13. clickworker. com

Follow me @sofia3973 for more AI Update.

[STEP MOM @stepmoom]

Ready for a wild fantasy experience?
Step into the dream world now 😈✨

https://t.co/RRVAJ5nfE8

#AI #Fantasy #DreamAI #VirtualStory #Roleplay #Fun

[Hasharia @hashariai]

Mother's Day With Stepson - Step Mom Comes First #stepmom #taboo #stepson #chudai #porn

[Ozedikus Nwanne @Ozedikus]

Everyone’s idea of heaven is based on what they lack here on earth

[Jobs with Aramide @AramideOyekunle]

Best YouTube Channels To Learn:

Web Development - Traversy Media
AWS - Code With Harry
SQL - Programming With Mosh
DevOps - Techworld with Nana
Blockchain - Telusko
AI/ML- Krish Naik
DBMS - edureka
Cybersecurity - John Hammond
Networking - David Bombal
Python - Code With Harry
React - Codevolution
UI/UX - GFXMentor
JavaScript - Traversy Media
Java - kunal kushwaha

[POOJA!!! @PoojaMedia]

Bro to bro, world cup & banter go come and go, nah your life go remain ooo😂

Omo, take life seriously this year,
I found this 3-Month Tech SCHOLARSHIP only for Africans and it’s closing in few days

They’re offering 17+ in-demand tech skills accredited by ACTD-USA + Certificate.

Closes Soon!
Apply here ASAP 👇🏽
https://t.co/nYgA2E97XZ

Please share this on your TL, someone might need this rare opportunity before it closes.

[Dandy @Dandythehusla]

🎬"I wanna have s£x with you" was all she got after requesting for a shock 😱

[Josias Lima @PrJopelim203]

O Tribunal do Crime

Rotineiramente, viralizam nas redes sociais vídeos de jovens sendo torturados ou executados sumariamente por membros de facções criminosas.

Em muitos casos, as motivações são banais: visitar parentes, participar de festas em comunidades rivais ou, até mesmo, fazer gestos supostamente alusivos a grupos rivais em fotografias.

Diante disso, o que mais choca é a apatia das autoridades, principalmente dos políticos, que não se mobilizam para criar mecanismos legais capazes de frear esses atos de terror.

É de extrema urgência que haja uma intervenção firme do Estado para cessar essa prática.

Afinal, se os criminosos se sentem no direito de aplicar a pena de morte, por que não tornar essa punição recíproca a quem a pratica?

https://t.co/6ODzxTbhr8

[1017 🚁🇲🇽ひ @bluegeaux]

did future gimmick and went out with two girls in one week and now none of them wanna talk to me

[MovieTalks🎬🍿 @jackofficial_01]

These series are not for the kids......

[𝘾𝙄𝙉𝙀𝙈𝘼 𝙆𝙪𝙡𝙩𝙪𝙧𝙚 @cinema_kulture]

Top 5 Wife Cheating Movies 🎥

These films explore how a single choice can change everything.

Thread 👇

[Kirk Borne @KirkDBorne]

XGBoost for Regression, Predictive Modeling, and Time Series Analysis — Learn how to build, evaluate, & deploy predictive models:
https://t.co/DsGwnEXyWF v/ @PacktDataML
—
My review:

🟠XGBoost is definitely the focal point and central contribution of this book, along with all those other things: Regression Trees, Predictive Modeling, Time Series Analysis, and Forecasting.

🟠This book’s added value comes in its thorough progression from start to finish with comprehensive coverage of all the major steps and issues in data science and machine learning modeling: data cleaning, imbalanced data, feature engineering, feature engineering pipeline, feature importance, categorical data encoding, model interpretability and explainability, ensembles, model training, model evaluation metrics, hyperparameter tuning, model deployment, and more - including a quick-start case study starter project that feeds into next-level projects.

🟠I highly recommend this broadly useful book for all levels of practitioners.

[Kirk Borne @KirkDBorne]

Simple Practical Data Cleaning #Python Code Snippets for messy data: https://t.co/d982YmvjUb
+
#DataCleaning Cookbook to prepare your data for analysis — PANDAS, NumPy, Matplotlib, scikit-learn, etc.: https://t.co/6AxvYTItfJ v/ @PacktDataML
—————
#DataScience #DataScientist

[Kirk Borne @KirkDBorne]

Data Cleaning and Exploration with Machine Learning: https://t.co/nqRGSXscoO v/ @PacktDataML @PacktPublishing
+
Visit the book's GitHub code repository: https://t.co/3nZVhNGNnj

[Cinema Zone 🍿 @CinemaZoneX]

🎬 Top 50 Greatest Tv Shows(Series) of All Time.

50. Banshee 🇺🇸
49. Slow Horses 🇬🇧
48. Gullak 🇮🇳
47. Death Note 🇯🇵
46. Rick and Morty 🇺🇸
45. The Bear 🇺🇸
44. The Shield 🇺🇸
43. South Park 🇺🇸
42. Lost 🇺🇸
41. The X-Files 🇺🇸
40. Scam 1992 🇮🇳
39. BoJack Horseman 🇺🇸
38. Dexter 🇺🇸
37. Curb Your Enthusiasm 🇺🇸
36. Money Heist 🇪🇸
35. Narcos 🇺🇸🇨🇴
34. Black Mirror 🇬🇧
33. Stranger Things 🇺🇸
32. Mr. Robot 🇺🇸
31. Hannibal 🇺🇸
30. Fargo 🇺🇸
29. Peaky Blinders 🇬🇧
28. Attack on Titan 🇯🇵
27. M*A*S*H 🇺🇸
26. The Simpsons 🇺🇸
25. Seinfeld 🇺🇸
24. The Twilight Zone 🇺🇸
23. Game of Thrones 🇺🇸
22. Fullmetal Alchemist: Brotherhood 🇯🇵
21. Avatar: The Last Airbender 🇺🇸
20. Severance 🇺🇸
19. Shōgun (2024) 🇺🇸🇯🇵
18. True Detective (S1) 🇺🇸
17. The Leftovers 🇺🇸
16. Deadwood 🇺🇸
15. Six Feet Under 🇺🇸
14. The West Wing 🇺🇸
13. Succession 🇺🇸
12. Sherlock 🇬🇧
11. Dark 🇩🇪
10. The Americans 🇺🇸
9. The Office 🇬🇧
8. Twin Peaks 🇺🇸
7. Chernobyl 🇺🇸🇬🇧
6. Better Call Saul 🇺🇸
5. Band of Brothers 🇺🇸
4. Mad Men 🇺🇸
3. The Wire 🇺🇸
2. The Sopranos 🇺🇸
1. Breaking Bad 🇺🇸

[Suraj Sharma @suraj_sharma14]

If I had 6 months to become an AI Analyst.

I'd do this.

Stage 1: Python + SQL for AI Analysis
pandas, numpy, SQL, Jupyter, API data ingestion, data cleaning, type validation, basic automation.

Stage 2: AI Literacy for Analysts
LLM fundamentals, RAG basics, prompt patterns, model limitations, cost/latency tradeoffs, failure modes.

Stage 3: Data Visualization + Storytelling
matplotlib, seaborn, plotly, Tableau/Power BI, dashboard design, executive summaries, insight framing.

Stage 4: AI-Enhanced EDA
LLM-assisted data profiling, automated anomaly detection, natural language querying, embedding-based clustering.

Stage 5: Prompt Engineering for Analysis
Writing analysis prompts, structured output schemas, few-shot examples for data tasks, prompt versioning, eval criteria.

Stage 6: RAG for Business Intelligence
Connecting internal docs/data to LLMs, citation tracking, grounding answers in source data, metadata filtering.

Stage 7: Evaluation + Quality for AI Insights
Accuracy vs usefulness, hallucination checks, source verification, confidence scoring, A/B testing AI-generated reports.

Stage 8: Automation + Workflow Integration
No-code/low-code AI tools, Zapier/Make + AI, scheduled reports, alerting on insights, human-in-the-loop validation.

Stage 9: Business Context + Stakeholder Alignment
Translating AI outputs to business impact, defining success metrics, managing expectations, prioritizing use cases.

Stage 10: Ethics + Responsible AI Analysis
Bias detection in outputs, PII handling, audit trails for AI-generated insights, documentation standards, compliance checks.

Stage 11: Open Source + Portfolio
Publish AI analysis case studies, write prompt libraries, record demo walkthroughs, share dashboard templates publicly.

Stage 12: Apply
AI Analyst, Business Intelligence Analyst AI, Product Analyst GenAI, Data Strategy Analyst, AI Operations Analyst.

Most people stay stuck watching tutorials.

Builders get hired.

[فيلم @1film26]

10 أفلام عن علاقات بين شاب وامرأة أكبر سناً

ثريد🎬🍿