Description
Deep Learning Masterclass with TensorFlow 2 Over 20 Projects, Deep Learning Masterclass with TensorFlow 2 with more than 20 projects is published by Udemy Academy. Deep learning is one of the most popular fields in computer science today. This software is used in various fields. With the release of much more efficient deep learning models in the early 2010s, we have seen great progress in things like computer vision, natural language processing, image generation, and signal processing. Demand for deep learning engineers is on the rise, and experts in this field command high salaries because of their value. However, getting started in this field is not easy. There is a lot of information out there, a lot of it is outdated and a lot of times it doesn’t cater to beginners.
In this course, we will take you on an amazing journey where you will master various concepts with a step-by-step and project-oriented approach. You can use Tensorflow 2 (the world’s most popular deep learning library made by Google) and Huggingface. We need to understand how to build very simple models (such as linear regression models to predict car prices, text classifiers to review videos, binary classifiers to predict malaria) using Tensorflow and Huggingface transformers. Let’s start with more advanced models (such as object recognition models with YOLO, text generation model with GPT2 and image generation with GANs).
What you will learn
- Basics of Tensors and Variables with Tensorflow
- Principles of Tensorflow and neural network training with TensorFlow 2.
- Convolutional neural networks used in malaria diagnosis
- Building more advanced Tensorflow models with functional API, model classification and custom layers
- Evaluation of classification models using different criteria such as: precision, recall, and F1-score
- Evaluation of classification model with density matrix and ROC curve
- Call Tensorflow, schedule the learning rate and check the model
- Reduce compatibility and over-compatibility with drop, regularize, increase data
- Data augmentation with TensorFlow using TensorFlow image and Keras layers
- Advanced amplification strategies such as Cutmix and Mixup
- Data Augmentation with Albummentation with TensorFlow 2 and PyTorch
- Disadvantages and advantages of customization in TensorFlow 2
Who is this course suitable for?
- Beginner Python developers are curious about using deep learning for computer vision and natural language processing.
- Deep learning for computer vision professionals who want to master how they work
- Anyone who wants to master the fundamentals of deep learning as well as practice deep learning for computer vision using best practices in TensorFlow.
- Computer vision professionals who want to learn how to build and train advanced computer vision models using deep learning.
- Natural language processing professionals who want to learn how to build and train advanced NLP models using deep learning.
- Anyone who wants to implement ML models
- People who want a hands-on approach to deep learning for computer vision, natural language processing, and voice recognition
Details of the course Deep Learning Masterclass with TensorFlow 2 Over 20 Projects
- Publisher: Udemy
- teacher : Neurallearn Dot AI
- English language
- Education level: all levels
- Number of courses: 313
- Training duration: 102 hours and 36 minutes
Head of the course seasons on 2023-5
Course prerequisites
- Basic Math
- Access to an internet connection, as we shall be using Google Colab (free version)
- Basic Knowledge of Python
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File(s) password: www.downloadly.ir
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