Prediktiva

● Launching and scaling the first Data Science Agency of LATAM 

Prediktiva empowers startups and SMEs to leverage the power of Machine Learning to make intelligent forward-looking projections that drive tangible business outcomes - in less than a month.

Founder, Head of Data Science

Notion

•  Designing and implementing Notion productivity systems to enhance the operational efficiency of fast-growing startups

Notion Certified Consultant

Vega Coffee

•  led the finance department and all associated strategic and operational functions as the 1st CFO hire, 
•  implemented tech and process automation initiatives to scale operations across three countries,
•  provided ongoing support during due diligence of Bridge and Seed Rounds

Chief Financial Officer

Liftit

•  developed a detailed understanding of unit economics to increase profitability and organic revenue by 57%
•  led strategic finance, sales, marketing, and operations across 5 countries 
•  right hand to the CEO in raising a $14.3m Series A and $22.5m Series B

Ruta N Medellin

•  coordinated Tech acceleration programs with a total budget of USD 1.2m
•  redesigned program structures & updated the acceleration methodology
•  supported more than 50 Series A & Seed-stage startups

Accelerator Manager

Suyo PBC

•  set up and directed finance function from scratch, including financial modelling, FP&A, budgeting & reporting, KPIs & OKRs tracking
•  developed and allocated operational budgets for the national expansion plan
•  supported the CEO during Seed-Round due-diligence and negotiations

Head Of Finance

UniCredit

•  participated in the origination, structuring, and negotiation of USD 100bn+ project finance infrastructure transactions, including preparation of full-blown models, negotiation of term sheets and operations due-diligence

Infrastructure & Power Project Finance - Senior Associate

𝗦𝗮𝘆 𝗴𝗼𝗼𝗱𝗯𝘆𝗲 𝘁𝗼 𝗵𝗼𝘂𝗿𝘀 𝗼𝗳 𝘁𝗲𝗱𝗶𝗼𝘂𝘀 𝗱𝗮𝘁𝗮 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝘁𝗵𝗶𝘀 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝘆 

Creating visualizations typically requires a bit of code and plenty of memorization, as different libraries, chart types, and customization options come with their own syntax and functions.

For example, when using Matplotlib or Seaborn, one would need to remember the syntax for creating the chart, the specific function for creating the chart type, and the different options for customizing the chart. 


𝗔𝘂𝘁𝗼𝘃𝗶𝘇 𝗶𝘀 𝗮𝗻 𝗼𝗽𝗲𝗻-𝘀𝗼𝘂𝗿𝗰𝗲 𝗣𝘆𝘁𝗵𝗼𝗻 𝗹𝗶𝗯𝗿𝗮𝗿𝘆 𝘁𝗵𝗮𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝘃𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗲 𝗮𝗻𝘆 𝗱𝗮𝘁𝗮 𝘀𝗲𝘁 𝘄𝗶𝘁𝗵 𝗷𝘂𝘀𝘁 𝗼𝗻𝗲 𝗹𝗶𝗻𝗲 𝗼𝗳 𝗰𝗼𝗱𝗲
 
The library uses machine learning to analyze the data and generate the most appropriate visualization, which can save analysts a significant amount of time and headache. 

Additionally, it also allows to quickly make changes to the generated visuals, giving the user control over the final outcome.
 
AutoViz can be a very powerful hack for data visualization, so don't wait any longer, go check it out today!


𝙥𝙞𝙥 𝙞𝙣𝙨𝙩𝙖𝙡𝙡 𝙖𝙪𝙩𝙤𝙫𝙞𝙯


#datascience #datavisualization 

🦾 Paolo Perrone

𝗜 𝗵𝗲𝗹𝗽 𝘀𝘁𝗮𝗿𝘁𝘂𝗽𝘀 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗠𝗟 𝗺𝗼𝗱𝗲𝗹𝘀 𝗶𝗻 𝟯𝟬 𝗱𝗮𝘆𝘀, 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗵𝗶𝗿𝗶𝗻𝗴 𝗮𝗻 𝗮𝗿𝗺𝘆 𝗼𝗳 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁𝘀

The viewer may see these photos as a carousel, instead of a grid. The photos will appear in the selected order. Learn more

👩‍💻Want to gain practical data science experience?

Here's a list of 𝟭𝟬 𝗳𝗿𝗲𝗲 𝘃𝗶𝗿𝘁𝘂𝗮𝗹 𝗶𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽𝘀 𝘄𝗶𝘁𝗵 𝘁𝗼𝗽 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 (BCG, British Airways, GE, KPMG, Tata, etc.) you can complete at your own pace to improve your skills and make your CV and LinkedIn stand out.

Share or comment 📣 to receive a message with the links 🤪

🚨🚨🚨
𝗖𝗹𝗶𝗰𝗸 𝘁𝗵𝗶𝘀 𝗹𝗶𝗻𝗸, 𝘀𝗰𝗿𝗼𝗹𝗹 𝗱𝗼𝘄𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗰𝗼𝗺𝗺𝗲𝗻𝘁 𝘁𝗼 𝗳𝗶𝗻𝗱 𝘁𝗵𝗲 𝘃𝗶𝗿𝘁𝘂𝗮𝗹 𝗶𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗹𝗶𝗻𝗸𝘀 

https://lnkd.in/eqtMDYxm


#datascience #career

Paolo Perrone - Free Virtual Internships

👩‍💻The path to becoming a data scientist can be difficult to navigate

With so many tools, notions and techniques it can feel overwhelming 🤕

If you didn't find the courage to take the leap or have felt discouraged, keep going, because this post is specifically for you

𝗔 𝗰𝗹𝗲𝗮𝗿, 𝘀𝘁𝗲𝗽-𝗯𝘆-𝘀𝘁𝗲𝗽 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, 𝗰𝗮𝗻 𝗺𝗮𝗸𝗲 𝗮𝗹𝗹 𝘁𝗵𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗶𝗻 𝘀𝗶𝗺𝗽𝗹𝗶𝗳𝘆𝗶𝗻𝗴 𝘁𝗵𝗲 𝗰𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗼𝗳 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲

By breaking down the learning process into manageable chunks, this roadmap will help you build a strong foundation for your data science journey

It will help you understand where you stand, 𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝗮𝗻𝗱 𝗼𝘃𝗲𝗿𝗰𝗼𝗺𝗲 𝘆𝗼𝘂𝗿 𝘄𝗲𝗮𝗸𝗻𝗲𝘀𝘀𝗲𝘀 𝗮𝗻𝗱 𝗯𝘂𝗶𝗹𝗱 𝗼𝗻 𝘆𝗼𝘂𝗿 𝘀𝘁𝗿𝗲𝗻𝗴𝘁𝗵𝘀, 𝘄𝗵𝗶𝗰𝗵 𝘄𝗶𝗹𝗹 𝗵𝗲𝗹𝗽 𝘆𝗼𝘂 𝘀𝘁𝗮𝘆 𝗺𝗼𝘁𝗶𝘃𝗮𝘁𝗲𝗱 𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗼𝘂𝘁 𝘁𝗵𝗲 𝗷𝗼𝘂𝗿𝗻𝗲𝘆


If this sounds like something you're interested in, show your support by resharing 🔁 or commenting 📣 and I'll send you a link to the resource 


𝗕𝗼𝗻𝘂𝘀 𝗽𝗼𝗶𝗻𝘁 🍄
If this post gets good traction, I'll also share a collection of data science projects next week, allowing you to apply your new knowledge and gain practical experience.


𝗟𝗲𝘁'𝘀 𝗱𝗼 𝘁𝗵𝗶𝘀 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿! 🚀

#datascience #datascientist #learning #career

Paolo Perrone The Complete Data Science Study Roadmap

𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝘁𝗵𝗲 𝗿𝗲𝗮𝗹 𝗔𝗜 𝗰𝗵𝗮𝗺𝗽𝗶𝗼𝗻 

- $1bn invested in OpenAI in 2019
- $10bn, 49% stake in OpenAI today
- Owns GitHub which released Copilot
- DALL-E now powers Bing Image Creator
- Will integrate GPT into Bing, Word, Outlook, and PowerPoint  
- Released VALL-E, a DALL-E that creates an AI voice from 3 seconds voice prompts 

Time to bring back Clippy?

𝗦𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗮 𝗰𝗮𝗿𝗲𝗲𝗿 𝗶𝗻 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗶𝘀 𝘀𝗶𝗺𝗽𝗹𝗲

But simplicity implies repetitive and boring

Here's where I see many people struggling to push through and failing

Remember: clarity and consistency of execution is what separates those who break through from those who don't

#datascience #datascientists #career 

Paolo Perrone - If I had to start from 0

let's check basic statistics understanding #dataanalyst & #datascientist

No alternative text description for this image

Navigating the no-code AI ecosystem just got easier with this comprehensive map 

No-code AI tools democratize access to data science, enabling more individuals and organizations to leverage this powerful technology

However, this carries the risk of creating a generation of practitioners who lack understanding and accountability, leading to potential security and ethical issues

For example, a no-code implementation used to screen job candidates could perpetuate and even amplify existing biases in the hiring process.


How do we ensure that no-code AI doesn't turn into a double edged sword?


#datascience #AI 

Credits for the image to Levity, find a link to the original post in the comment

Had a brief conversation with ChatGPT, and it's almost ready to take over the world

I had an Excel joke

But it crashed and I'm still trying to recover it 🤪

#datascience  #excel

Low-code data science platforms are getting better by the day

Don’t underestimate them

#datascience

Correlation is the math

Causation is the meaning we give to math

#datascience

Taking courses is the most socially accepted vanity metrics for data scientists

I give zero kudos for taking 10 courses a year

I give you massive kudos for learning efficiently and smart implementation

#datascientists #career

Many founders aren't hiring from Harvard 

They're hiring from LinkedIn

#datascience #career

Especially around the holidays 🎄 

I'm easy to please 😀

𝟱 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 𝘄𝗶𝘁𝗵 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗜𝗱𝗲𝗮𝘀 😉💯

📉Linear Regression ➡️ Predict movie success based on factors such as budgets, cast, director and marketing

📈Logistic Regression ➡️ Predict the likelihood of customer making a purchase based on their browsing, purchasing history and demographics, 

🗞️ SVM ➡️ Predict music genres by analyzing tempo, rhythm, chord progression

🏛️ KNN ➡️ Predict the likelihood of a customer churning based on their usage patterns and demographics

🧮 Naive Bayes ➡️ Predict book genre based on its plot summary and cover image

Point: possibilities are endless, start building today

#datascientists #machinelearning 


𝗣𝗲𝗼𝗽𝗹𝗲 𝗱𝗼𝗻'𝘁 𝗳𝗮𝗶𝗹 𝘁𝗼 𝗮𝗰𝗵𝗶𝗲𝘃𝗲 𝘁𝗵𝗲𝗶𝗿 𝗴𝗼𝗮𝗹𝘀
 
They fail at planning and tracking progress towards their goals

After researching the best goal setting methodologies for years, I've developed a framework that has benefitted me enormously

These slides will teach you how to:

1️⃣ escape the frustration of missed resolutions 
2️⃣ move towards your goals with more confidence and clarity
3️⃣ maximize your impact and progressively take on more ambitious and challenging goals

Ready?

#datascientists #goals #planning 

Paolo Perrone - Ultimate Goal Setting Guide

𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗷𝗮𝗿𝗴𝗼𝗻 𝗲𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 

1️⃣ 𝗘𝗻𝘀𝗲𝗺𝗯𝗹𝗲  

👇 

Ensemble methods are a powerful tool that can significantly improve the accuracy and robustness of your models

Ensemble methods either train multiple individual models on the same data, or a single model on different subsets of the data

The predictions of the individual models are then combined in some way to produce a final prediction 

Ensemble methods can be applied to a wide range of model types and can be trained using different techniques such as boosting, bootstrapped ensembles, and bagging. 

So if you want to take your machine learning performance to the next level, you consider giving ensemble methods a try! 

What else do you want to know about this powerful technique?

Drop it in the comments 👇

🚨   𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝗶𝘀 𝗻𝗼𝘁 𝗮𝗻 𝗶𝗻𝗳𝗮𝗹𝗹𝗶𝗯𝗹𝗲 𝗼𝗿𝗮𝗰𝗹𝗲 🚨 

It's a sophisticated mimic able to generate slick language that reads as if a human wrote it 

But ChatGPT lacks any real understanding of the content it produces and presents both facts and falsehoods with the same level of confidence 

𝗣𝗼𝗶𝗻𝘁: 𝘄𝗲'𝗹𝗹 𝗮𝗹𝗹 𝗯𝗲 𝘁𝗵𝗲 𝗯𝗲𝘁𝗮 𝘁𝗲𝘀𝘁𝗲𝗿𝘀 𝗳𝗼𝗿 𝘁𝗵𝗲𝘀𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 

#datascience #artificialintelligence

Communicating less (but more meaningful) information is better than providing detailed information (jargon) without explanation  
 
𝗧𝗵𝗿𝗲𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 (& 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀) 𝘁𝗼 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗮𝘀 𝗮 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 👇
 

❓ 1️⃣ what data is relevant to this audience?
not all data and insight are relevant to every audience


❓ 2️⃣ what level of technical detail is appropriate for this audience?
not every audience has the technical understanding of a subject like you do


❓ 3️⃣ are there any specific terms or acronyms the audience is not familiar with?
not recognizing an audience's understanding of industry terminology leads  to misunderstandings


𝗣𝗼𝗶𝗻𝘁: 𝘄𝗵𝗲𝗻 𝗽𝗿𝗲𝘀𝗲𝗻𝘁𝗶𝗻𝗴 𝗱𝗮𝘁𝗮, 𝗹𝗲𝘀𝘀 𝗰𝗮𝗻 𝗯𝗲 𝗺𝗼𝗿𝗲

What else do you do to get your message across loud  and clear?

#datascience #datascientists #dataanalyst

To all fellas who were into data before it was cool 😉

#data #datascientist

Taplio

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