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The Complete Deep Learning & Computer Vision Course in 2020

The Complete Deep Learning & Computer Vision Course in 2020

The Complete Deep Learning & Computer Vision Course in 2020 Learn Deep Learning & Computer Vision with Python, Tensorflow 2.0, OpenCV, FastAI. Object Detection & GAN and much more!


What you'll learn

  • Using Latest Tools & Techniques in Deep Learning & Computer Vision
  • Learning how to used the latest Tensorflow 2.0
  • How to apply Transfer Learning, Ensemble Learning, using GPUs & TPUs
  • How to work & win Kaggle Competitions
  • Learning to use FastAI
  • How to use Generative Adversarial Networks
  • How to use Weights & Biases for recording Experiments
  • Learning to use Detectron2 for Object Detection
  • Making Machine Learning Web Application from Scratch
  • Learn how to use OpenCV for Computer Vision
  • How to make Real World Applications & Deploy into Cloud
  • Learning Techniques like Object Detection, Classification & Generation
  • Learning how to use Heroku for deploying ML models
  • Working on Kaggle Competitions & Kaggle Kernels
  • Exploring & Visualizing Datasets using popular libraries like Matplotlib & Plotly.
  • Learinng how to use libraries like Pandas, Sklearn, Numpy
  • Creating Advance Data Pipelines using Tensorflow for training Deep Learning Models
  • Setting up Environment & Project for Deep Learning & Computer Vision


This Brand New and Modern Deep Learning & Computer Vision Course will teach you everything you will need to know to become a Computer Vision Expert.

Deep Learning & Computer Vision is currently one of the most increasing fields of Artificial Intelligence and Companies like Google, Apple,

Facebook, Amazon are highly investing in this field. Deep Learning & Computer Vision jobs are increasing day by day & provide some of the highest paying jobs all over the world.

If We Want Machines to Think, We Need to Teach Them to See.-Fei Fei Li, Director of Stanford AI Lab and Stanford Vision Lab

Computer Vision allows us to see the world & process digital images & videos to extract useful information to do a certain task from classification, object detection, and much more. Python is one of the most popular used programming language in Deep Learning and Computer Vision.

All the tools, techniques & technologies used in this course -

  1. Learning Computer Vision & Deep Learning Fundamentals
  2. Setting up Anaconda, Installing Libraries & Jupyter Notebook
  3. Learning fundamentals of OpenCV & Numpy - Reading images, Colorspaces, Drawing & Callbacks
  4. Advanced OpenCV - Image Preprocessing, Geometrical transformations ,Perspective transformations & affine transformations ,image blending & pyramids, image gradients & thresholding, Canny Edge Detector and contours
  5. Working with videos in OpenCV -  Using webcam, Haar Cascades & Object Detection, Lane Detection
  6. Deep Learning & How Neural Network Works ? - Artificial neural networks, Convolution Neural Networks & Transfer Learning

Image Classification - Plant leaf Classification

  • Working on very recent Kaggle Competitions
  • Using Google Colab & Kaggle Kernels
  • Using latest Tensorflow 2.0 & Keras
  • Using Keras Data Generators & Data Argumentation
  • Using Transfer Learning & Ensemble learning
  • Using State of The Art Deep Learning Models
  • Using GPU & TPU for Model Training
  • Hyperparameter Tuning
  • Using Weights & Biases for recording Deep Learning experimentations
  • Saving & Loading Models
  • Creating a Weights & Biases Report & Showcasing the Project!

Object Detection - Wheat heads Detection

  • Working on Kaggle Competitions, again!
  • Using Facebook's Detectron2 for Object Detection
  • Creating COCO Dataset from scratch
  • Training Faster RCNN Model and Custom Weights & Biases callback
  • Using Retinanet
  • Saving & Loading Detectron2 models

Generative Adversarial Networks - Creating Fake Leaf Images

  • Learning How Generative Adversarial Networks works
  • Using FastAI
  • Creating & Training Generative Adversarial Networks
  • Making Fake Images using GAN

Making ML Web Application

  • Getting started with Streamlit
  • Creating an ML Web Application from scratch using Streamlit
  • making a React Web Application

Deploying ML Applications

  • Learning how to use Cloud Services to Deploy Models & Applications
  • Using Heroku
  • Learning how to Open Source Projects on GitHub
  • How to showcase your projects to impress boss & employes & Get Hired!

A lot of bonus lectures!

  • This is what included in the package
  • All lecture codes are available for downloadable for free
  • 110+ HD video lectures ( over 50 more to come very soon! )
  • Free support in course Q/A
  • All videos with English captions available

This course is for you if..

  • ... you want to learn the Latest Tools & Techniques used in Deep Learning & Computer Vision
  • ... you want to get more experience to Win Kaggle Competitions
  • ... you want to get started with Computer Vision to become a Computer Vision Engineer
  • .. you are interested in learning Image Classification, Object Detection, Generative Adversarial Networks, Making & Deploying Machine Learning Applications

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