Machine Learning Fundamentals

«Machine Learning Fundamentals» è un corso online di Programmazione di livello intermedio, tenuto da InsightLearn — contenuto di test su InsightLearn. Il percorso comprende 6 lezioni organizzate in 2 sezioni, per una durata complessiva di 2h 25m. Learn the core concepts of machine learning including supervised, unsupervised, and reinforcement learning.

Descrizione del corso

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Learn the core concepts of machine learning including supervised, unsupervised, and reinforcement learning. Build and evaluate real models using Python and scikit-learn.

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⚠️ DISCLAIMER COPYRIGHT: Questo corso utilizza contenuti video con licenza Creative Commons a scopo educativo e di test. Tutti i diritti rimangono ai rispettivi autori. Non è richiesto alcun abbonamento per la visione. Su richiesta dell'autore, il contenuto verrà rimosso immediatamente. Contatto: [email protected]

Cosa imparerai

  • Build ML models, evaluate performance, apply algorithms to real datasets

Requisiti

  • Basic Python programming knowledge required

Programma del corso

  1. Lesson 1.1 - Welcome to the course (15 min)

    Course overview, learning path, and setting up Python environment with Anaconda and scikit-learn.

  2. Lesson 1.2 - Basic concepts (20 min)

    Supervised vs unsupervised learning, training/test split, features and labels explained.

  3. Lesson 1.3 - First practice (25 min)

    Build your first classifier using the Iris dataset with a decision tree in scikit-learn.

  4. Lesson 2.1 - Advanced topics (20 min)

    Ensemble methods: random forests, gradient boosting, and hyperparameter tuning with GridSearchCV.

  5. Lesson 2.2 - Case study (30 min)

    End-to-end ML pipeline: predicting house prices with feature engineering and cross-validation.

  6. Lesson 2.3 - Final project (35 min)

    Build and deploy a complete ML model on a real-world dataset of your choice.

Dalle lezioni

Estratto della trascrizione di «Lesson 1.1 - Welcome to the course»

So let's start with commenting outlines. You can use a hashtag to comment out a single line and triple speech marks to comment out multiple lines. Next we have variables. Variables store data and have a unique name. There are a couple of rules for naming your variables, plus here to take a look. As I was saying, they store data and the four main types are here. Strings which are an array of characters, integers which is any whole number, negative or positive, floats, any number doesn't have to be whole, and booleans which can only be true or false. These are the main four and there are a couple more which you probably won't use. Now you need…

Estratto della trascrizione di «Lesson 1.2 - Basic concepts»

Hey, what's going on everybody? It's your bro. Hope you're doing well. And in this video, I'm going to help you get started with Python. So sit back, relax, and enjoy the show. If you wouldn't mind, please like, comment, and subscribe. One like equals one prayer for the YouTube algorithm. I'm going to tell you why you need to learn Python. It's the easiest programming language to learn, as well as being the most popular in the world right now. And according to Glassdoor, the salary for new Python developers in the United States is $64,000. If any of this sounds good to you, well then let's get started. If you need to download Python, go to python.org slash…

Estratto della trascrizione di «Lesson 1.3 - First practice»

So let's start with commenting outlines. You can use a hashtag to comment out a single line and triple speech marks to comment out multiple lines. Next we have variables. Variables store data and have a unique name. There are a couple of rules for naming your variables, plus here to take a look. As I was saying, they store data and the four main types are here. Strings, which are an array of characters, integers, which is any whole number, negative or positive, floats, any number doesn't have to be whole, and booleans, which can only be true or false. These are the main four, and there are a couple more which you probably won't use. Now you need…

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Domande frequenti

Quanto dura il corso Machine Learning Fundamentals?

Il corso dura 2h 25m in totale, con 6 lezioni suddivise in 2 sezioni, da seguire online al proprio ritmo.

Serve esperienza pregressa?

Il corso è di livello intermedio. I requisiti indicati dal docente sono: Basic Python programming knowledge required.

Il corso rilascia un certificato?

Sì: al completamento del corso ricevi un certificato di completamento verificabile online.