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