Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today we're expanding our simple Logistic Regression...
to classy more than 2 classes! 👇🏻 By default, Logistic Regression is like a coin toss - heads or tails, A or B.

But what if you have multiple classes?

That's where we adapt our model for MULTIPLE CHOICES!
There are two main ways:

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today we're expanding our simple Logistic Regression...
to classy more than 2 classes! 👇🏻 By default, Logistic Regression is like a coin toss - heads or tails, A or B.

But what if you have multiple classes?

That's where we adapt our model for MULTIPLE CHOICES!
There are two main ways:

Ever feel like Python's simplicity is almost poetic?

Let's dive into the elegant world of Python's structures.

A journey of poetic logic awaits! 🚀 1️⃣ 𝗧𝗛𝗘 𝗔𝗥𝗧 𝗢𝗙 𝗪𝗛𝗜𝗧𝗘𝗦𝗣𝗔𝗖𝗘
Python's beauty lies in its simplicity.

Unlike other languages cluttered with braces and keywords, Python uses plain old indentation to define a program's structure.

It's like poetry for coders! 📖

Struggling to trust every chart you see? 🤔📊

Then, you better learn the 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 𝗼𝗳 𝗽𝗿𝗼𝗽𝗼𝗿𝘁𝗶𝗼𝗻𝗮𝗹 𝗶𝗻𝗸 in Data Visualization

Today, I'm unveiling why some charts can be misleading. 💥 First things first, ever heard of the term "ink" in data visualization?

It's not about the ink in your pen.

It refers to any part of a visualization that stands out from the background.

Think lines, bars, points, and even text. 🖋️

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

We are going back to the basics to simplify ML algorithms.
... today's turn is Logistic Regression! 👇🏻 1️⃣ 𝗟𝗢𝗚𝗜𝗦𝗧𝗜𝗖 𝗥𝗘𝗚𝗥𝗘𝗦𝗦𝗜𝗢𝗡
It is a binary classification model used to classify our input data into two main categories.

It can be extended to multiple classifications... but today we'll focus on a binary one.

Also known as Simple Logistic Regression.

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

We are going back to the basics to simplify ML algorithms.
... today's turn is Multiple Linear Regression! 👇🏻 In MLR, imagine you're baking.

You've got different ingredients or variables.

You need the perfect recipe (model) for your cake (prediction).

Each ingredient's quantity (coefficient) affects the taste (outcome).

Ever felt lost in Python's universe of data types? 🌌

Then dive into the basics with me today!

Today we're exploring Booleans, Integers, and Floats – the core elements in Python's data type galaxy! 🚀🐍 These data types are like the atoms of Python.

We start with them individually and later combine them into larger structures like lists and dictionaries.

It's a journey from simplicity to complexity!

Struggling to craft effective charts? 🤔📊

Then, you better understand the 𝗚𝗲𝘀𝘁𝗮𝗹𝘁 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 in Data Visualization.

Today, I'm unveiling why some charts are intuitive while others are confusing 💥 Think of DataViz as your GPS in the world of numbers.

It turns complex data into clear, actionable insights.

But... why do some charts enlighten us while others don't?

The Gestalt Theory explains how our brains perceive patterns and how to take advantage of them.

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

We are going back to the basics to simplify ML algorithms.
... today's turn is Multiple Linear Regression! 👇🏻 4️⃣ 𝗠𝗨𝗟𝗧𝗜-𝗩𝗔𝗥𝗜𝗔𝗕𝗟𝗘 📐
We can add multiple variables to perform a MULTIPLE Linear Regression.

The core theory is the same: We still use a linear function to predict our target.

But we can track N independent values

So we can consider both Height and Gender ➡️ N=2

Ever felt confused by SQL's execution flow? 🤔

Then you better stay with me!

Today let's exemplify SQL's execution order with a simple query👇🏻 1️⃣ 𝗦𝗧𝗔𝗥𝗧𝗜𝗡𝗚 𝗙𝗥𝗢𝗠 𝗢𝗨𝗥 𝗥𝗔𝗪 𝗧𝗔𝗕𝗟𝗘
We use a dummy table with the salary of employees depending on their field and experience,

🎯 Our main goal?
Understand the field that earns the most.

Want to become a SQL Pro and no idea where to start?

Then, you better...

👉 SAVE these 9 steps to become an SQL Pro! 👈 1️⃣ 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝗤𝗟:
Understand basics like SELECT, WHERE, JOIN, and ORDER BY.

We all need to start from the basics!

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today I am starting with a new ML model
... so it is the turn of the Support Vector Machine! 👇🏻 0️⃣ 𝗥𝗘𝗖𝗔𝗣
SVM is a ML method that finds the optimal hyperplane separating classes by maximizing margin, using support vectors to ensure the greatest distance between class data points.

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today we're expanding our simple Logistic Regression...
to classy more than 2 classes! 👇🏻 By default, Logistic Regression is like a coin toss - heads or tails, A or B.

But what if you have multiple classes?

That's where we adapt our model for MULTIPLE CHOICES!
There are two main ways:

Are you the one crafting charts to communicate your data?

Then you better stay with me! 🤓

Today let's dive into visual encoding and their key role in DataViz! 👇🏻 Charts are composed of two core components:
- Data
- Visuals

But how do we convert this data into a visual representation?

Say hi to visual encodings! 👋🏻

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today we're exemplifying Logistic Regression...
all set to classify two adorable penguin species! 👇🏻🐧🔍 1️⃣ 𝗗𝗔𝗧𝗔 𝗚𝗔𝗧𝗛𝗘𝗥𝗜𝗡𝗚 𝗣𝗛𝗔𝗦𝗘
We're using Kaggle to find robust data for our flippered friends.

Meet our stars: the dapper Gentoo and the lovely Adelie!

Like biologists in the wild, we'll use data points to distinguish between them.

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today I am starting with a new ML model
... so it is the turn of Logistic Regression! 👇🏻 1️⃣ 𝗟𝗢𝗚𝗜𝗦𝗧𝗜𝗖 𝗥𝗘𝗚𝗥𝗘𝗦𝗦𝗜𝗢𝗡
It is a binary classification model used to classify our input data into two main categories.

It can be extended to multiple classifications... but today we'll focus on a binary one.

Also known as Simple Logistic Regression.

Ever feel like Python's simplicity is almost poetic?

Let's dive into the elegant world of Python's structures.

A journey of poetic logic awaits! 🚀 1️⃣ 𝗧𝗛𝗘 𝗔𝗥𝗧 𝗢𝗙 𝗪𝗛𝗜𝗧𝗘𝗦𝗣𝗔𝗖𝗘
Python's beauty lies in its simplicity.

Unlike other languages cluttered with braces and keywords, Python uses plain old indentation to define a program's structure.

It's like poetry for coders! 📖

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today I am starting with a new ML model
... so it is the turn of Logistic Regression! 👇🏻 0️⃣ 𝗥𝗘𝗖𝗔𝗣
Logistic Regression is your go-to for predicting whether something is YES or NO.

It uses a slick curve to calculate probabilities and a special formula to minimize errors, ensuring your predictions are on point!

Ever stared at a chart and wondered what secret sauce makes it... well, a chart?

It's time to decode the magic behind those bars, lines, and pies.

Today's turn is for what (two) core elements compose the DataViz world! 🎨📊 𝗪𝗛𝗔𝗧 𝗠𝗔𝗞𝗘 𝗔𝗟𝗟 𝗖𝗛𝗔𝗥𝗧𝗦 𝗧𝗢 𝗥𝗘𝗔𝗟𝗟𝗬 𝗕𝗘... 𝗔 𝗖𝗛𝗔𝗥𝗧?
All charts share two main traits:

- They all communicate data.

- They all have a graphic design.

Struggling with Machine Learning algorithms? 🤖

Then you better stay with me! 🤓

Today I am starting with a new ML model
... so it is the turn of Logistic Regression! 👇🏻 1️⃣ 𝗟𝗢𝗚𝗜𝗦𝗧𝗜𝗖 𝗥𝗘𝗚𝗥𝗘𝗦𝗦𝗜𝗢𝗡
It is a binary classification model used to classify our input data into two main categories.

It can be extended to multiple classifications... but today we'll focus on a binary one.

Also known as Simple Logistic Regression.

Struggling with long and complex SQL queries?

Last week, we dived into CTEs and their advantages.

Today, let's see them in action with a real-world example!👇🏻 Imagine we have a table of all Airbnb apartments in Barcelona.

Our goal? 🎯

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗔𝗶𝗿𝗯𝗻𝗯'𝘀 𝗽𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗶𝗻 𝗲𝗮𝗰𝗵 𝗻𝗲𝗶𝗴𝗵𝗯𝗼𝘂𝗿𝗵𝗼𝗼𝗱.

And SQL is the perfect tool to do so!