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Machine Learning courses

Machine learning courses cover algorithms and concepts for enabling computers to learn from data and make decisions without explicit programming. Build your skills in NLP, deep learning, MLOps and more.

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Prova DataCamp for Business

Recommended for Machine Learning beginners

Build your Machine Learning skills with interactive courses, curated by real-world experts

Corso

Capire il Machine Learning

BasicLivello di competenza
2 ore
11.1K
Unintroduzione allapprendimento automatico senza bisogno di programmare.

Programma

Fondamenti di apprendimento automatico in Python

16 ore
6.9K
Impara larte dellapprendimento automatico e diventa un maestro nella predizione, nel riconoscimento dei modelli e negli albori dellapprendimento profondo e dellapprendimento per rinforzo.

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Sfoglia i corsi e programmi su Machine Learning

Corso

Apprendimento supervisionato con scikit-learn

IntermedioLivello di competenza
4 ore
20K
Sviluppa le tue competenze di machine learning con scikit-learn in Python. Usa dataset reali in questo corso interattivo e realizza previsioni efficaci.

Corso

Capire il Machine Learning

BasicLivello di competenza
2 ore
11.1K
Unintroduzione allapprendimento automatico senza bisogno di programmare.

Corso

Apprendimento non supervisionato in Python

IntermedioLivello di competenza
4 ore
5.3K
Impara a raggruppare, trasformare, visualizzare ed estrarre informazioni utili da set di dati non etichettati usando scikit-learn e scipy.

Corso

Concetti MLOps

IntermedioLivello di competenza
2 ore
3.3K
Scopri come MLOps porta i modelli di machine learning da notebook locali a modelli funzionanti in produzione con reale valore aziendale.

Corso

Classificatori lineari in Python

IntermedioLivello di competenza
4 ore
1.6K
In questo corso imparerai i dettagli dei classificatori lineari come la regressione logistica e SVM.

Corso

Analisi di cluster in Python

IntermedioLivello di competenza
4 ore
1.4K
In questo corso imparerai lapprendimento non supervisionato usando tecniche come il clustering gerarchico e k-means con la libreria SciPy.

Corso

Extreme Gradient Boosting with XGBoost

IntermedioLivello di competenza
4 ore
1.3K
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Corso

Introduzione a MLflow

AvanzatoLivello di competenza
4 ore
1.3K
Scopri come usare MLflow per semplificare la creazione di applicazioni di machine learning e approfondisci tracking, progetti e modelli.

Corso

Machine Learning con PySpark

AvanzatoLivello di competenza
4 ore
1.1K
Impara a fare previsioni dai dati con Apache Spark, usando alberi decisionali, regressione logistica, regressione lineare, insiemi e pipeline.

Corso

Deployment e ciclo di vita in MLOps

AvanzatoLivello di competenza
4 ore
1K
In questo corso scoprirai il moderno framework MLOps, esplorando il ciclo di vita e limplementazione dei modelli di machine learning.

Corso

Machine Learning end-to-end

IntermedioLivello di competenza
4 ore
972
Entra nel mondo dellapprendimento automatico e scopri come progettare, addestrare e implementare modelli end-to-end.

Corso

Validazione dei modelli in Python

IntermedioLivello di competenza
4 ore
961
Impara le basi della validazione dei modelli, le tecniche di validazione e inizia a creare modelli validati e super efficaci.

Corso

Supervised Learning in R: Regression

IntermedioLivello di competenza
4 ore
851
In questo corso imparerai come prevedere cosa succederà usando la regressione lineare, i modelli additivi generalizzati, le foreste casuali e xgboost.

Corso

CI/CD per Machine Learning

AvanzatoLivello di competenza
5 ore
837
Migliora il tuo sviluppo di machine learning con CI/CD usando GitHub Actions e il controllo delle versioni dei dati

Corso

Natural Language Processing con spaCy

IntermedioLivello di competenza
4 ore
661
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Corso

Modelli ARIMA in Python

AvanzatoLivello di competenza
4 ore
627
Scopri i modelli ARIMA in Python e diventa un esperto nellanalisi delle serie temporali.

Corso

Machine Learning for Finance in Python

IntermedioLivello di competenza
4 ore
601
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

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    Frequently asked questions

    Is machine learning easy to learn?

    DataCamp's beginner machine learning courses are a lot of hands-on fun, and they provide an excellent foundation for machine learning to advance your career or business. Within weeks, you'll be able to create models and generate predictions and insights. You'll also learn foundational knowledge of Python and R and the fundamentals of artificial intelligence.

    After that, the learning curve gets a bit steeper. Machine learning careers require a deeper understanding of statistics, math, and software engineering, all of which can be mastered at DataCamp.

    What is machine learning used for?

    In a nutshell, machine learning is a type of artificial intelligence whose algorithms, as they acquire data, produce analytical models and make predictions with little to no human intervention.

    It's difficult to find an industry that doesn't use machine learning. For example, marketers use machine learning to forecast returns on investments in marketing campaigns. Likewise, purchasing departments use machine learning to predict needed inventory.

    Businesses of all kinds use machine learning to predict customer behavior, map supply chains, and forecast revenues. Machine learning is used to predict health outcomes and to improve patient satisfaction. Machine learning helps scientists model climate change scenarios, including possible solutions.

    More specifically, machine learning is used in smart devices, search engines, and streaming services (when Netflix suggests a show or movie based on your viewing history, that's machine learning).

    What jobs can you get with machine learning skills?

    Machine learning skills are valuable in programming, data science, and other computer engineering disciplines. In addition, machine learning is a must for anyone wanting to work in robotics!

    Not all jobs that require machine learning are in tech though. For example, linguists use machine learning to track ever-changing languages and dialects. In addition, business departments, such as marketing, accounting, logistics, and purchasing, to name a few, increasingly need machine learning experts to help them make informed business decisions. Knowing machine learning can give you a step up in nearly any position, as modeling and predicting are critical business needs.

    Are machine learning skills in demand?

    Yes, machine learning skills are in high demand. According to a report by the World Economic Forum, demand for AI and ML specialists is expected to grow by 40% between 2023 and 2027.

    How much math do I need to take a machine learning course?

    If you're looking to develop a high-level understanding of machine learning concepts, you don't need much math. If you want to dive deeper and make machine learning your career (as opposed to an added value to your existing career), a foundation in statistics and algebra is helpful. If you don't have a mathematical background, that's okay. We'll teach you everything you need, and our instructors are a lot less scary than your high school calculus teacher.

    Do I need to download machine learning software to learn on DataCamp?

    You do not need to download anything while learning with DataCamp. All the tools we use are web-based.

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