Master Deep Learning for Computer Vision in TensorFlow[2025]

About Master Deep Learning for Computer Vision in TensorFlow[2025]

Deep Learning

is a hot topic today! This is because of the

impact

it's having in several industries. One of fields in which deep learning has the most influence today is

Computer Vision.

Object detection, Image Segmentation, Image Classification, Image Generation & People Counting To understand why

Deep Learning based Computer Vision

is so popular; it suffices to take a look at the different domains where giving a computer the power to understand its surroundings via a camera has changed our lives. Some applications of Computer Vision are:

Helping doctors more efficiently carry out

medical diagnostics

enabling farmers to

harvest their products with robots

, with the need for very little human intervention,

Enable

self-driving cars

Helping quick response surveillance with

smart CCTV systems

, as the cameras now have an eye and a brain

Creation of art

with GANs, VAEs, and Diffusion Models

Data analytics in sports, where

players' movements are monitored

automatically using sophisticated computer vision algorithms. The

demand for Computer Vision engineers is skyrocketing

and experts in this field are

highly paid

, because of their value. In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be using

Tensorflow 2

(the world's most popular library for deep learning, built by Google) and

Huggingface.

We shall start by understanding how to build very simple models (like Linear regression model for

car price prediction

and binary classifier for

malaria prediction

) using Tensorflow to much more advanced models (like object detection model with

YOLO

and Image generation with

GANs

). After going through this course and carrying out the different projects, you will develop the skill sets needed to develop modern deep learning for computer vision solutions that big tech companies encounter. _You will learn:_

The Basics of TensorFlow

(Tensors, Model building, training, and evaluation)

Deep Learning algorithms like

Convolutional neural networks and Vision Transformers

Evaluation of Classification Models (

Precision, Recall, Accuracy, F1-score, Confusion Matrix, ROC Curve

)

Mitigating overfitting with

Data augmentation

Advanced Tensorflow concepts like

Custom Losses and Metrics, Eager and Graph Modes and Custom Training Loops, Tensorboard

Machine Learning Operations

(MLOps

) with Weights and Biases

(Experiment Tracking, Hyperparameter Tuning, Dataset Versioning, Model Versioning)

Binary Classification with

Malaria detection

Multi-class Classification with

Human Emotions Detection

Transfer learning with modern Convnets (

Vggnet, Resnet, Mobilenet, Efficientnet

) and Vision Transformers

(VITs)

Object Detection with YOLO

(You Only Look Once)

Image Segmentation with

UNet

People Counting with

Csrnet

Model Deployment (

Distillation, Onnx format, Quantization, Fastapi, Heroku Cloud

)

Digit generation with

Variational Autoencoders

Face generation with

Generative Adversarial Neural Networks

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.

Enjoy!!!