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7 Courses293 Tasks 4.8
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Python from Zero to Hero
6 Courses169 Tasks 4.7
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4 Courses115 Tasks 4.7
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6 Courses101 Tasks 4.5
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4 Courses143 Tasks 4.7
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7 Courses346 Tasks 4.7
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6 Courses309 Tasks 4.7
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5 Courses146 Tasks 4.7
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project
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.
5.0
(1)
Only for Ultimate
2 hours
10 chaptersAdvanced
3 STUDYING NOW
course
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.
4.8
(17)
4 hours 25 chaptersAdvanced
7 STUDYING NOW
course
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 β 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.
4.7
(41)
4 hours 32 chaptersIntermediate
21 STUDYING NOW
course
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.
5.0
(2)
4 hours 24 chaptersAdvanced
3 STUDYING NOW
course
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!
4.2
(13)
4 hours 28 chaptersIntermediate
4 STUDYING NOW
project
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.
new
Only for Ultimate
1 hour 6 chaptersAdvanced
course
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.
new
3 hours 20 chaptersAdvanced
6 STUDYING NOW
project
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.
5.0
(1)
Only for Ultimate
2 hours 10 chaptersAdvanced
3 STUDYING NOW
course
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.
4.8
(17)
4 hours 25 chaptersAdvanced
7 STUDYING NOW
course
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 β 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.
4.7
(41)
4 hours 32 chaptersIntermediate
21 STUDYING NOW
course
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.
5.0
(2)
4 hours 24 chaptersAdvanced
3 STUDYING NOW
course
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!
4.2
(13)
4 hours 28 chaptersIntermediate
4 STUDYING NOW
project
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.
new
Only for Ultimate
1 hour 6 chaptersAdvanced
course
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.
new
3 hours 20 chaptersAdvanced
6 STUDYING NOW
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