- Decision Trees
- Artificial Neural Network
- Logistic Regression
- Recommender Systems
- Linear Regression
- Regularization to Avoid Overfitting
- Gradient Descent
- Supervised Learning
- Logistic Regression for Classification
- Xgboost
- Tensorflow
- Tree Ensembles
Programa de cursos integrados Aprendizagem Automática
#BreakIntoAI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng
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O que você vai aprender
Build ML models with NumPy & scikit-learn, build & train supervised models for prediction & binary classification tasks (linear, logistic regression)
Build & train a neural network with TensorFlow to perform multi-class classification, & build & use decision trees & tree ensemble methods
Apply best practices for ML development & use unsupervised learning techniques for unsupervised learning including clustering & anomaly detection
Build recommender systems with a collaborative filtering approach & a content-based deep learning method & build a deep reinforcement learning model
Habilidades que você terá
Sobre este Programa de cursos integrados
Projeto de Aprendizagem Aplicada
By the end of this Specialization, you will be ready to:
• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.
• Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression.
• Build and train a neural network with TensorFlow to perform multi-class classification.
• Apply best practices for machine learning development so that your models generalize to data and tasks in the real world.
• Build and use decision trees and tree ensemble methods, including random forests and boosted trees.
• Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection.
• Build recommender systems with a collaborative filtering approach and a content-based deep learning method.
• Build a deep reinforcement learning model.
- Basic coding (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra)
- Other math concepts will be explained
- Basic coding (for loops, functions, if/else statements) & high school-level math (arithmetic, algebra)
- Other math concepts will be explained
Como funciona o programa de cursos integrados
Fazer cursos
Um programa de cursos integrados do Coursera é uma série de cursos para ajudá-lo a dominar uma habilidade. Primeiramente, inscreva-se no programa de cursos integrados diretamente, ou avalie a lista de cursos e escolha por qual você gostaria de começar. Ao se inscrever em um curso que faz parte de um programa de cursos integrados, você é automaticamente inscrito em todo o programa de cursos integrados. É possível concluir apenas um curso — você pode pausar a sua aprendizagem ou cancelar a sua assinatura a qualquer momento. Visite o seu painel de aprendiz para controlar suas inscrições em cursos e progresso.
Projeto prático
Todos os programas de cursos integrados incluem um projeto prático. Você precisará completar com êxito o(s) projeto(s) para concluir o programa de cursos integrados e obter o seu certificado. Se o programa de cursos integrados incluir um curso separado para o projeto prático, você precisará completar todos os outros cursos antes de iniciá-lo.
Obtenha um certificado
Ao concluir todos os cursos e completar o projeto prático, você obterá um certificado que pode ser compartilhado com potenciais empregadores e com sua rede profissional.

Este Programa de cursos integrados contém 3 cursos
Supervised Machine Learning: Regression and Classification
In the first course of the Machine Learning Specialization, you will:
Advanced Learning Algorithms
In the second course of the Machine Learning Specialization, you will:
Unsupervised Learning, Recommenders, Reinforcement Learning
In the third course of the Machine Learning Specialization, you will:
oferecido por

deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.

Universidade de Stanford
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
Perguntas Frequentes – FAQ
Qual é a política de reembolso?
Posso me inscrever em um único curso?
Existe algum auxílio financeiro disponível?
Posso fazer o curso gratuitamente?
Este curso é realmente 100% on-line? Eu preciso assistir alguma aula pessoalmente?
What is machine learning?
What is the Machine Learning Specialization about?
What will I learn in the Machine Learning Specialization?
What background knowledge is necessary for the Machine Learning Specialization?
Who is the Machine Learning Specialization for?
How long does it take to complete the Machine Learning Specialization?
Who created the Machine Learning Specialization?
What makes the Machine Learning Specialization so unique?
How is the new Machine Learning Specialization different from the original course?
I'm a complete beginner. Can I take this Specialization?
I enrolled in but couldn’t complete the original Machine Learning course. Can I take the new Machine Learning Specialization?
I’ve completed the original Machine Learning course. Should I take the new Machine Learning Specialization?
I’ve completed the Deep Learning Specialization. Should I take the new Machine Learning Specialization?
Is this a standalone course or a Specialization?
Do I need to take the courses in a specific order?
How much does the Specialization cost?
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How do I get a receipt to get this reimbursed by my employer?
I want to purchase this Specialization for my employees. How can I do that?
Vou ganhar créditos universitários por concluir a Especialização?
Will I receive a certificate at the end of the Specialization?
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