Introduction to Neural Networks
Cours
591 Apprenants déjà inscrits- Understand the core concepts behind neural networks and their structure.
- Grasp the role and functionality of a single neuron and perceptron layers in artificial intelligence.
- Comprehend activation functions, along with forward and backward propagation techniques.
- Explore applications of deep learning in real-world scenarios.
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Ce cours comprend 3 modules
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.- Single Neuron ImplementationAperçu
- Challenge: Creating a NeuronAperçu
- Perceptron LayersAperçu
- Challenge: Creating a PerceptronAperçu
- Forward PropagationAperçu
- Loss FunctionAperçu
- Backward PropagationAperçu
- Backpropagation ImplementationAperçu
- Model TrainingAperçu
- Challenge: Training the PerceptronAperçu
- Model EvaluationAperçu
- Challenge: Evaluating the PerceptronAperçu
- Neural Network with scikit-learnAperçu
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Pourquoi les gens choisissent Codefinity pour leur carrière

Kwizera Mugisha
The teaching methodology at Codefinity is excellent, and I particularly appreciate how it has prepared me to handle real-world coding problems. Currently, I am delving into Node.js and eagerly anticipate building full-stack projects that integrate all the knowledge I have gained.

Sherry Barnes-Fox
My first course was 4 hours, I did it in a few days, "nugget-style. The instructions are very clear and easy to understand. There is even a hint to help you get the answer, and if you still cannot get the answer, then you can display the answer. I love the learning style that is used, it engages me.

Bill Wagner
I have really liked the browser-based lessons that allow me to code within the lesson. The RUN button allows me to test the code I write before submitting for a grade.

Stephanie Chan
As I went through the first course of the Python track, I liked the way the course was lay out (in easy and digestible modules) with little exercises at the end of each concept.

Daniel Chinea
I have gained a lot of practical and logical thinking skills, along with patience for myself and confidence in myself that I can learn programming.

Steve Bruening
The learning was progressive and made it easy to follow along and make progress. I could feel my skills increasing and building on each other as the course went along.
Avis des apprenants
4.8
19 avis
5
84%
4
11%
3
5%
2
0%
1
0%
Affichage 3 de 19 avis
Massimo Gattoni
5
Évalué le Jun 21, 2025
Great job boys!
Yan Bodnya
4
Évalué le Jun 6, 2025
A bit of mix between complexity and practice. Also if doing as part of the track would benefit of better relationship between courses
Athanasios Samaras
4
Évalué le Feb 12, 2025
Good hints provided, nice skeleton code
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