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Recognizing Handwritten Digits

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.

Introduction to Neural Networks

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.

ML Introduction with scikit-learn

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.

Introduction to NLP

Let's explore the fundamentals of Natural Language Processing (NLP) as you delve into text preprocessing techniques and various text models used to represent text data. You will gain practical insights and hands-on experience with the tools and methods essential for analyzing and interpreting textual data effectively. This course equips you with the skills to transform raw text into meaningful information, paving the way for advanced applications in AI and machine learning.

Classification with Python

In machine learning, classification is used in predictive modeling to assign input data with a class label. Sounds difficult? Don't worry! Let's cope with this! Welcome to the ML!

Logistic Regression Mastering

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.

Computer Vision Essentials

Comprehensive introduction to Computer Vision, focusing on machine perception and interpretation of visual data. Covers image preprocessing, feature extraction, object detection, and deep learning techniques used in modern vision systems.

Introduction to Reinforcement Learning

Reinforcement Learning (RL) is a powerful branch of machine learning focused on training intelligent agents through interaction with their environment. In this course, you'll learn how agents gradually discover effective behaviors through trial and error. Beginning with core concepts like Markov decision processes and multi-armed bandits, you'll work your way through dynamic programming, Monte Carlo methods, and temporal difference learning.

PyTorch Essentials

Learn the fundamental and advanced concepts needed to work with PyTorch efficiently. Gain a solid understanding tensors, including creation, operations, and reshaping. Explore the essentials of gradients, backpropagation, and linear regression before moving on to handling datasets. Master the skill needed build, train, and evaluate neural networks.

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Web Development with C#

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Python from Zero to Hero

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Game Development with Unity

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Become a React Developer

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Excel Essentials

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Java Essentials

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Full Stack Web Development

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Frontend Development Foundations

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Mastering Data Visualization

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Machine Learning Mastery

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C++ Mastery

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7 Kurser

376 Opgaver

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7 Kurser

345 Opgaver

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6 Kurser

308 Opgaver

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5 Kurser

146 Opgaver

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Recognizing Handwritten Digits

Introduction to Neural Networks

ML Introduction with scikit-learn

Introduction to NLP

Classification with Python

In machine learning, classification is used in predictive modeling to assign input data with a class label. Sounds difficult? Don't worry! Let's cope with this! Welcome to the ML!

Logistic Regression Mastering

Computer Vision Essentials

Introduction to Reinforcement Learning

PyTorch Essentials

Recognizing Handwritten Digits

Introduction to Neural Networks

ML Introduction with scikit-learn

Introduction to NLP

Classification with Python

In machine learning, classification is used in predictive modeling to assign input data with a class label. Sounds difficult? Don't worry! Let's cope with this! Welcome to the ML!

Logistic Regression Mastering

Computer Vision Essentials

Introduction to Reinforcement Learning

PyTorch Essentials

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