In this course you will learn everything that is needed for developing and applying Deep Learning models to
your own data. All relevant fields like Regression, Classification, CNNs, RNNs, GANs, NLP, Recommender
Systems, and many more are covered.
PyTorch Ultimate 2024: From Basics to Cutting-Edge
Become an professional making use of the most famous Deep Learning framework PyTorch
PyTorch Ultimate 2024: From Basics to Cutting-Edge
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What you will learn
analyze all applicable components of PyTorch from easy fashions to modern-day models
installation your mannequin on-premise and to Cloud
Transformers
Natural Language Processing (NLP), e.g. Word Embeddings, Zero-Shot Classification, Similarity Scores
CNNs (Image-, Audio-Classification; Object Detection)
Style Transfer
Recurrent Neural Networks
Autoencoders
Generative Adversarial Networks
Recommender Systems
adapt top-notch algorithms like Transformers to customized datasets
improve CNN fashions for photograph classification, object detection, Style Transfer
strengthen RNN models, Autoencoders, Generative Adversarial Networks
study about new frameworks (e.g. PyTorch Lightning) and new fashions like OpenAI ChatGPT
Requirements
primary Python knowledge
Description
PyTorch is a Python framework developed via Facebook to strengthen and installation Deep Learning models. It is one of the most famous Deep Learning frameworks nowadays.
In this route you will analyze the whole thing that is wanted for growing and making use of Deep Learning fashions to your very own data. All applicable fields like Regression, Classification, CNNs, RNNs, GANs, NLP, Recommender Systems, and many extra are covered. Furthermore, country of the artwork fashions and architectures like Transformers, YOLOv7, or ChatGPT are presented.
It is necessary to me that you research the underlying ideas as nicely as how to enforce the techniques. You will be challenged to handle troubles on your own, earlier than I existing you my solution.
In my direction I will train you:
Introduction to Deep Learning
excessive degree understanding
perceptrons
layers
activation functions
loss functions
optimizers
Tensor handling
introduction and precise aspects of tensors
automated gradient calculation (autograd)
Modeling introduction, incl.
Linear Regression from scratch
perception PyTorch mannequin training
Batches
Datasets and Dataloaders
Hyperparameter Tuning
saving and loading models
Classification models
multilabel classification
multiclass classification
Convolutional Neural Networks
CNN theory
strengthen an photo classification model
layer dimension calculation
photo transformations
Audio Classification with torchaudio and spectrograms
Object Detection
object detection theory
advance an object detection model
YOLO v7, YOLO v8
Faster RCNN
Style Transfer
Style switch theory
creating your very own fashion switch model
Pretrained Models and Transfer Learning
Recurrent Neural Networks
Recurrent Neural Network theory
developing LSTM models
Recommender Systems with Matrix Factorization
Autoencoders
Transformers
Understand Transformers, which includes Vision Transformers (ViT)
adapt ViT to a customized dataset
Generative Adversarial Networks
Semi-Supervised Learning
Natural Language Processing (NLP)
Word Embeddings Introduction
Word Embeddings with Neural Networks
Developing a Sentiment Analysis Model based totally on One-Hot Encoding, and GloVe
Application of Pre-Trained NLP models
Model Debugging
Hooks
Model Deployment
deployment strategies
deployment to on-premise and cloud, particularly Google Cloud
Miscellanious Topics
ChatGPT
ResNet
Extreme Learning Machine (ELM)
Enroll proper now to research some of the coolest methods and enhance your profession with your new skills.
Best regards,
Bert
Who this route is for:
Python builders willing to analyze one of the most fascinating and in-demand methods