Introduction to NLP

Introduction to SQL

4 horas

41 capítulos

This course is for you if you are new to SQL, you want to quickly learn how to get the most out of SQL and you want to learn how to use SQL in your own application development.

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Pandas First Steps

4 horas

34 capítulos

Pandas is an extremely user-friendly library for data analysis. It's also designed to handle large datasets, using data structures like DataFrame and Series. This makes it an invaluable tool for Data Science. In this guide, you'll get acquainted with a range of statistical functions, including how to find correlations, modes, medians, and maximum and minimum values within a dataset. You'll also learn how to handle missing values and manipulate specific values, as well as how to remove them.

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Exploratory Data Analysis of Nobel Prizes

1 hora

6 capítulos

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.

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Image Synthesis Through Generative Networks

3 horas

19 capítulos

Discover the artistry behind image generation using generative networks in our course. From theory to practice, delve into the world of generative networks, unlocking the secrets to crafting captivating images from data.

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Text Summarization with TF-ISF

2 horas

12 capítulos

In this project, we aim to design and implement a text summarizer utilizing the Python programming language as our foundational tool. To achieve this, we will be leveraging the powerful Natural Language Toolkit which is instrumental in the processing and analysis of textual data.

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NumPy in a Nutshell

3 horas

21 capítulos

NumPy is one of the basic packages for scientific computing in Python. The 'NumPy in a Nutshell' course will introduce you to such a powerful tool as NumPy, which is convenient for working with arrays of different sizes. After completing this course, you will be able to easily work with matrices, using various functions. In addition, during the course, you will learn basic methods for working with arrays that simplify code writing.

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Recognizing Handwritten Digits

2 horas

10 capítulos

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.

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Advanced Techniques in pandas

4 horas

33 capítulos

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

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Introduction to Neural Networks

3 horas

19 capítulos

Neural networks are powerful algorithms inspired by the structure of the human brain that are used to solve complex machine learning problems. You will build your own Neural Network from scratch to understand how it works. After this course, you will be able to create neural networks for solving classification and regression problems using the scikit-learn library.

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Natural Language Handling

1 hora

11 capítulos

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.

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Identifying Fake News

1 hora

7 capítulos

In this project, we are going to classify news and identify the fake ones.

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ML Introduction with scikit-learn

4 horas

33 capítulos

Machine Learning is now used everywhere. Want to learn it yourself? This course is an introduction to the world of Machine learning for you to learn basic concepts, work with Scikit-learn – the most popular library for ML and build your first Machine Learning project. This course is intended for students with a basic knowledge of Python, Pandas, and Numpy.

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