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Deep Learning Odyssey
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Start with the core principles of how neural networks work and progress to building and training your own models using popular frameworks like TensorFlow and PyTorch. Gain practical experience by applying neural networks to tasks in computer vision and sequence modeling, and work with cutting-edge architectures. Show more
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Try Codefinity TeamsWhat you will learn
- Understand the core concepts behind neural networks and how they learn from data.
- Build and train neural networks using TensorFlow and PyTorch.
- Apply deep learning techniques to solve real-world computer vision tasks.
- Work with convolutional neural networks (CNNs) for image classification and feature extraction.
- Use recurrent neural networks (RNNs) to model sequences and time series data.
- Explore practical workflows for developing and testing deep learning models.
- 92 chapters
- 14 hours
- 153 tasks
Trusted by employees of leading companies
Learning track content
Module 1 / Introduction to Neural Networks
First, we will discuss what a neural network is and how it works. And also consider the scope of its application.
Next, we will try to build our own neural network and see how efficiently it copes with learning. We will also consider a ready-made solution from the scikit-learn library.
- Single Neuron ImplementationPreview
- Challenge: Creating a NeuronPreview
- Perceptron LayersPreview
- Challenge: Creating a PerceptronPreview
- Forward PropagationPreview
- Loss FunctionPreview
- Backward PropagationPreview
- Backpropagation ImplementationPreview
- Model TrainingPreview
- Challenge: Training the PerceptronPreview
- Model EvaluationPreview
- Challenge: Evaluating the PerceptronPreview
- Neural Network with scikit-learnPreview
Finally, we will give you some additional useful information on how to understand which model to use and what types of neural networks there are. To complete the course, you will be tested on your acquired knowledge.
Module 2 / Introduction to TensorFlow
You will gain a foundational understanding of TensorFlow's primary components - Tensors. You'll delve into the nature and applications of tensors, familiarize yourself with tensor properties, and acquire knowledge in essential mathematical operations.
- Welcome to TensorFlowPreview
- Introduction to TensorsPreview
- Tensor PropertiesPreview
- Applications of TensorsPreview
- BatchesPreview
- Creating TensorsPreview
- Data TypesPreview
- Basic Operations: ArithmeticPreview
- Basic Operations: Linear AlgebraPreview
- Challenge: Creating a Neural Network LayerPreview
- TransformationsPreview
- Reduction OperationsPreview
- Quiz: TensorFlow BasicsPreview
You'll learn how TensorFlow operates and the ways to improve its performance. By the end of this module, you'll be well-equipped to implement basic neural networks or other tensor calculations, using only the TensorFlow library without any extras.
Module 3 / PyTorch Essentials
Explore the fundamentals of PyTorch, focusing on tensors—the core data structure used for computations. You will learn about tensor creation, random initialization, mathematical operations, and shape manipulation.
- What is PyTorch?Preview
- Introduction to TensorsPreview
- Tensor Creation FunctionsPreview
- Challenge: Initializing TensorsPreview
- Creating Random TensorsPreview
- Challenge: Initializing Model Weights and BiasesPreview
- Mathematical Operations with TensorsPreview
- Challenge: Performing Mathematical OperationsPreview
- Shapes and Dimensions in PyTorchPreview
- Challenge: Reshaping TensorsPreview
Explore key concepts for training models in PyTorch, including computing gradients and performing multi-step backpropagation. Master linear regression as a foundational machine learning model and introduces handling datasets efficiently.
Discover how to build, train, and evaluate neural networks using PyTorch. You will learn how to define a simple feedforward neural network, optimize its parameters through training, and assess its performance.
Module 4 / Computer Vision Essentials
Computer vision enables machines to interpret and analyze visual data, mimicking human perception. This section covers the basics of image representation, color models, and mathematical foundations essential for understanding how computers process images. You'll explore real-world applications, from autonomous vehicles to medical imaging, and learn how Computer vision integrates with AI and machine learning.
OpenCV is a powerful library for image manipulation and computer vision tasks. This section covers essential techniques like image filtering, transformations, edge detection, and segmentation. You'll learn how to perform blurring, thresholding, contour detection, and feature extraction to enhance and analyze images efficiently.
CNNs process visual data using convolution, pooling, and activation layers to extract features for tasks like image classification and object detection. Key components include padding, convolution for feature extraction, pooling for complexity reduction, and activation for non-linearity. Popular architectures like AlexNet, VGG, and ResNet power AI in healthcare, autonomy, and security.
Object detection is a fundamental task in computer vision that involves identifying and localizing objects within an image. Unlike image classification, which assigns a single label to an entire image, object detection not only classifies objects but also determines their positions using bounding boxes. This section covers key techniques and algorithms used in object detection, ranging from traditional methods to deep learning-based approaches like YOLO and U-Net.
Computer vision has significantly advanced over the years, shifting from basic image processing methods to complex deep learning techniques. This section delves into the latest innovations in computer vision, focusing on transfer learning, facial recognition, and image generation. We will explore the benefits of pre-trained models on performance, the principles of facial recognition technology, and the way AI creates images through deep learning.
Requirements
- A computer with a browser - all browsers are supported.
- Your enthusiasm to enhance your tech skills.
- Everything else needed to start learning and practicing is already included in this course.
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The material is good, there is a lot to learn, all in order to become better and the main thing is to learn what you want....
Matteo Comune
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Thanks to them I'm learning a lot faster because they help you to understand everything from scratch. It's the best website that helps people with no background in IT...
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great course for beginners
great course for beginners, they test your knowledge in every lesson...
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I am enjoying my Codefinity experience learning Python. The self-paced way of learning is great because I can fit it into my schedule...
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Codefinity is a comprehensive learning tool to help you develop your skills as a software engineer or data scientist. The exercises are fun and a good way to sharpen your skills...
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Well designed for total beginners, incremental progress and makes me feel confident....
_Gracy
it's simply perfectly well explained
it's simply perfectly well explained! so far I have not experienced any difficulty because everything is so well managed...
Ruslan Kravchuk
The main thing is to learn and not give up
The material is good, there is a lot to learn, all in order to become better and the main thing is to learn what you want....
Matteo Comune
Thanks to them I'm learning a lot…
Thanks to them I'm learning a lot faster because they help you to understand everything from scratch. It's the best website that helps people with no background in IT...
Yuliana Cadavid
great course for beginners
great course for beginners, they test your knowledge in every lesson...
Elpunzon
I am enjoying my Codefinity experience…
I am enjoying my Codefinity experience learning Python. The self-paced way of learning is great because I can fit it into my schedule...
Alexandru Alexandru
Is nice to learn from codefinity
Is nice to learn from codefinity. Its easy and have good examples on what I learned here...
jacob Templet
Easy to follow along with and provides…
Easy to follow along with and provides challenge in my every day life. The challenge keeps me wanting to learn day after day...
Elan
Codefinity is a comprehensive learning…
Codefinity is a comprehensive learning tool to help you develop your skills as a software engineer or data scientist. The exercises are fun and a good way to sharpen your skills...
Thibault
First time learning how to code
First time learning how to code and successfully doing so with codefinity - thank you...
Adrien Morel
Well designed for total beginners
Well designed for total beginners, incremental progress and makes me feel confident....
_Gracy
it's simply perfectly well explained
it's simply perfectly well explained! so far I have not experienced any difficulty because everything is so well managed...
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