Cursos de Machine Learning

Conducting Exploratory Data Analysis of Nobel Prizes

1 hora

6 capítulos

Intermedio

We will delve into the concept of Exploratory Data Analysis (EDA) and explore its critical role within every Data Analysis process, particularly focusing on the analysis of Nobel Prizes. EDA serves as a foundational step that enables data scientists and analysts to uncover patterns, anomalies, and insights from data through visual and statistical methods.

Ver detalles

Extracting Text Meaning using TF-IDF

2 horas

12 capítulos

Intermedio

This project focuses on the design and implementation of a robust text summarizer, built using Python. By harnessing the capabilities of Python’s Natural Language Toolkit (NLTK), participants will gain hands-on experience in processing and analyzing textual data. The project covers a range of NLP techniques essential for text summarization. Participants will develop skills in parsing text and extracting meaningful content, learning how to filter essential information from large volumes of text.

Ver detalles

Manipulating and Combining PDFs

1 hora

9 capítulos

Principiante

In this project, we will study how to manipulate and extract data from PDF files, such as text and images, and combine multiple PDF files into a single document.

Ver detalles

Recognizing Handwritten Digits

2 horas

10 capítulos

Avanzado

In this project, our primary objective will be to delve into the identification of handwritten digits through the application of machine learning algorithms. This endeavor aims to harness the power of machine learning to effectively interpret and understand handwritten digits, showcasing the potential of these algorithms in processing and analyzing complex visual information.

Ver detalles

Identifying the Most Frequent Words in Text

1 hora

11 capítulos

Principiante

In this project, we will be utilizing the capabilities of the Natural Language Toolkit (NLTK), a versatile and comprehensive library in Python designed for working with human language data. Our focus will encompass several core areas of natural language processing: tokenization, stemming, tagging and parsing. These NLTK features will form the backbone of our text processing and analysis tasks, making it an essential tool in our project for handling and extracting meaningful insights from language data.

Ver detalles

Time Series Essentials

1 hora

8 capítulos

Intermedio

In this project, we are going to understand what a Time Series is and which are its main features.

Ver detalles

Automating Data Collection from Web Sources

1 hora

7 capítulos

Intermedio

In this project, we are going to understand how to create a simple web scraper in Python.

Ver detalles

Getting into NumPy Basics

1 hora

7 capítulos

Intermedio

In this project, we will delve into the fundamentals of NumPy, exploring its core features and uncovering the reasons behind its significant impact on scientific computing. By understanding its architecture and capabilities, we will grasp why it is considered an essential tool for data scientists, researchers, and developers working in the realm of data analysis, machine learning, and beyond.

Ver detalles

Organizing Date and Time Data for Analysis and Applications

1 hora

7 capítulos

Principiante

In this project, we are going to understand how to handle Date and Times in Python.

Ver detalles

Excel Automation with Python

1 hora

11 capítulos

Intermedio

In this project, we will study how to create, modify, and extract data from Excel spreadsheets using Python code.

Ver detalles