Description

In this course, we shall look at core Deep Learning concepts and apply our knowledge to solve real world problems in Computer Vision and Natural Language Processing using the Python Programming Language and TensorFlow 2. We shall explain core Machine Learning topics like Linear Regression, Logistic Regression, Multi-class classification and Neural Networks. If you’ve gotten to this point, it means you are interested in mastering Deep Learning For Computer Vision and Deep Learning, using your skills to solve practical problems.

You may already have some knowledge on Machine learning, Computer vision, Natural Language Processing or Deep Learning, or you may be coming in contact with Deep Learning for the very first time. It doesn’t matter from which end you come from, because at the end of this course, you shall be an expert with much hands-on experience.

You shall work on several projects like object detection, image generation, object counting, object recognition, disease detection, image segmentation, Sentiment Analysis, Machine Translation, Question Answering, Image captioning, speech recognition and more, using knowledge gained from this course.

If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.

Here are the different concepts you’ll master after completing this course.

   Fundamentals Machine Learning.
   Essential Python Programming
   Choosing Machine Model based on task
   Error sanctioning
   Linear Regression
   Logistic Regression
   Multi-class Regression
   Neural Networks
   Training and optimization
   Performance Measurement
   Validation and Testing
   Building Machine Learning models from scratch in python.
   Overfitting and Underfitting
   Shuffling
   Ensembling
   Weight initialization
   Data imbalance
   Learning rate decay
   Normalization
   Hyperparameter tuning
   TensorFlow Installation
   Training neural networks with TensorFlow 2
   Imagenet training with TensorFlow
   Convolutional Neural Networks
   VGGNets
   ResNets
   InceptionNets
   MobileNets
   EfficientNets
   Transfer Learning and FineTuning
   Data Augmentation
   Callbacks
   Monitoring with Tensorboard
   Breast cancer detection
   Object detection with YOLO
   Image segmentation with UNETs
   People counting
   Generative modeling with GANs
   Image generation
   IMDB Dataset
   Sentiment Analysis
   Recurrent Neural Networks.
   LSTM
   GRU
   1D Convolution
   Bi directional RNN
   Word2Vec
   Machine Translation
   Attention Model
   Transformer Network
   Vision Transformers
   LSH Attention
   Image Captioning
   Question Answering
   BERT Model
   HuggingFace
   Deploying A Deep Learning Model with Google Cloud Functions

Who this course is for:

   Beginner Python Developers curious about Applying Deep Learning for Computer vision and NLP
   Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
   Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
   Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood.
   NLP practitioners who want to learn how state of art Natural Language Processing models are built and trained using deep learning.
   Anyone who wants to master deep learning fundamentals and also practice deep learning for NLP using best practices in TensorFlow 2.
   Deep Learning for NLP Practitioners who want gain a mastery of how things work under the hood.

ENjoy!!!

Let’s make this course as interactive as possible, so that we still gain that classroom experience.
Who this course is for:

   Beginner Python Developers curious about Applying Deep Learning for Computer vision and Natural Language Processing
   Deep Learning for Computer vision Practitioners who want gain a mastery of how things work under the hood
   Anyone who wants to master deep learning fundamentals and also practice deep learning for computer vision using best practices in TensorFlow.
   Computer Vision practitioners who want to learn how state of art computer vision models are built and trained using deep learning.
   Natural Language Processing practitioners who want to learn how state of art NLP models are built and trained using deep learning.
   Anyone wanting to deploy ML Models
   Learners who want a practical approach to Deep learning for Computer vision, Natural Language Processing and Sound recognition

Requirements

   Basic Math
   No Programming experience. You will learn everything you need to know

Last Updated 6/2022