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Machine Learning with Python: from Linear Models to Deep Learning (edX)

Feb 1st 2023
Machine Learning with Python: from Linear Models to Deep Learning (edX)
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An in-depth introduction to the field of machine learning, from linear models to deep learning and reinforcement learning, through hands-on Python projects. Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), [...]

Supervised Machine Learning: Regression and Classification (Coursera)

Jan 30th 2023
Supervised Machine Learning: Regression and Classification (Coursera)
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In the first course of the Machine Learning Specialization, you will: 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 [...]

Data Engineering and Machine Learning using Spark (Coursera)

Jan 30th 2023
Data Engineering and Machine Learning using Spark (Coursera)
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Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others. In this short course [...]

O que é ciência de dados? (Coursera)

A arte de revelar os insights e as tendências dos dados existe desde a antiguidade. Os antigos egípcios usavam os dados do censo para aumentar a eficiência da cobrança de impostos e previam com precisão a cheia do Nilo todos os anos. Desde então, as pessoas que trabalham com [...]

Introduction to Statistics (Coursera)

Stanford's "Introduction to Statistics" teaches you statistical thinking concepts that are essential for learning from data and communicating insights. By the end of the course, you will be able to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You [...]

Build Regression, Classification, and Clustering Models (Coursera)

Jan 30th 2023
Build Regression, Classification, and Clustering Models (Coursera)
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In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, [...]
Jan 30th 2023
Course Auditing
41.00 EUR/month

Simple Regression Analysis in Public Health (Coursera)

Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between [...]

Data Modeling and Regression Analysis in Business (Coursera)

The course will begin with what is familiar to many business managers and those who have taken the first two courses in this specialization. The first set of tools will explore data description, statistical inference, and regression. We will extend these concepts to other statistical methods used for prediction [...]

Supervised Learning: Regression (Coursera)

Jan 30th 2023
Supervised Learning: Regression (Coursera)
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This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, [...]

Machine Learning with Python (Coursera)

This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Second, you will [...]