Recognizing Handwritten Digits

2 hours

10 chapters

Advanced

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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Identifying Spam Emails

2 hours

11 chapters

Advanced

We are going to classify emails as spam or non-spam by analyzing the content of the emails. We will preprocess the text data using techniques like tokenization and vectorization, then apply machine learning to build and evaluate a classification model, namely Logistic Regression. By the end of the project, we aim to develop a reliable tool for identifying spam emails.

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Classifying Tweet Sentiments

3 hours

20 chapters

Advanced

We are going to classify tweets according to their sentiment, determining whether they express positive, negative, or neutral emotions. We will employ natural language processing techniques to preprocess the text data, and machine learning algorithms to build and evaluate sentiment classification models. By the end of the project, we aim to achieve a robust sentiment analysis tool that can accurately categorize the emotional tone of various tweets.

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Predicting Profitable Euro-Dollar Exchange Signals

3 hours

20 chapters

Advanced

In this course, we will examine the currency exchange rate relative to the euro. Our analysis will include Exploratory Data Analysis (EDA), generating visualizations, and developing a strategy to determine opportune moments for purchasing dollars. This strategy will involve trend detection techniques and constructing moving average curves to identify potential profit opportunities.

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Identifying Fake News

2 hours

9 chapters

Advanced

We are going to identify fake news by analyzing text data and determining whether articles are legitimate or deceptive. We will preprocess the text data using natural language processing techniques and apply machine learning algorithms to build and evaluate classification models. By the end of the project, we aim to develop an effective tool that can accurately distinguish between real and fake news.

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Logistic Regression Mastering

1 hour

6 chapters

Advanced

Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. In this project, we will leverage logistic regression to classify data into two distinct categories. The process will involve data preprocessing, model training, evaluation, and tuning to achieve optimal performance.

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