Ensemble Learning is an advanced machine learning technique that combines multiple models to improve overall predictive performance and decision-making when solving real-life tasks.

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

Identify fake news by analyzing text data and determining whether articles are legitimate or deceptive. Preprocess the text data using natural language processing techniques and apply machine learning algorithms to build and evaluate classification models. Develop an effective tool that can accurately distinguish between real and fake news.

Master Recurrent neural networks and their advanced variants like LSTMs and GRUs using PyTorch. Gain hands-on experience processing sequential data for practical applications. Apply these powerful models to tackle real-world challenges in time series forecasting and various Natural language processing tasks.

In this project, we are going to understand the career tracks of Data Scientists.

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.

To study many applied disciplines, it is necessary to have basic knowledge of higher mathematics and linear algebra. Mathematics is often used in data analysis, system modeling, building machine learning models, etc. Let's look at some of the most important topics and learn how to use the mathematical apparatus to solve real problems.

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

Visualization is one of the most common ways of representing data. By using different kinds of plots (like scatter-plot, histogram, bar charts, and so on) you can find some insights in your data, or approve/reject some assumption/hypothesis. In this course, you will be introduced to the matplotlib library, and learn how to build different charts.

Data Analysis with Excel provides a practical guide to mastering the most essential data management, manipulation, and analysis techniques using Microsoft Excel. You'll gain proficiency in Excel's powerful capabilities, progressing through data analysis methods, and creating dynamic visualizations and interactive dashboards. By the end, you'll learn to automate reporting and apply advanced analytics, equipping you to make informed, data-driven decisions efficiently.

Get ready to build an awesome fighting game featuring cool animations and a big boss battle! Learn Unity's animation system to create smooth player movements and powerful attacks. Dive into enemy AI, shaping their behaviors from following to rage states. Improve your game with simple UI elements, cool effects, and sounds. Finally, share your game with others to play it.

Learn how to build applications using the Django ORM framework. This is the next step in expanding your knowledge of Django development.

Dive into the world of neural network development with an immersive program that blends foundational knowledge with advanced techniques. The course emphasizes hands-on learning, providing learners with the opportunity to apply these techniques. Additionally, you will face numerous data preprocessing tasks and real-world examples of neural network training, so stay prepared and motivated, as it will present a significant challenge for you.

This course is a comprehensive and practical online program designed to equip individuals with the knowledge and skills necessary to conduct effective A/B tests. In this course, participants will learn the fundamental principles of A/B testing, including experimental design, sample size determination, hypothesis testing, and statistical analysis.

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