Deep Learning and AI with Python for Beginners

Name: Deep Learning and AI with Python for Beginners
Rating: 4.3 (119 reviews)

Beginners course if you are passionate about Artificial Intelligence & want to enter Deep Learning world using Python

Created byMazhar Hussain

Last updated 3/2024

English

English [Auto],

What you'll learn

Deep Learning and AI with Python Starting from Basic Concepts
Artificial Neurons - Building Blocks of Deep Learning and AI
Deep Convolutional Neural Networks (ResNet and AlexNet)
Learn UNet Deep Learning Encoder-Decoder Architecture
Learn PSPNet Deep Learning Architecture
Learn PAN Deep Learning Architecture
Learn Region-Based Convolutional Neural Networks (RCNNs)
Setting-up Google Colab for Writing Python Code
Data Preprocessing using different Image Transformations with Python
Deep Learning Models to Perform Single and Multi-label Image Classification

Course content

10 sections • 20 lectures • 1h 21m total length

Introduction to Course2:14
Explore how deep learning uses large neural networks to learn from data and perform image analysis, with Python and PyTorch powering applications in computer vision, natural language processing, autonomous vehicles.

Region-Based Convolutional Neural Networks (RCNNs)7:38
Explore region-based convolutional neural networks (rcnn) for object detection and instance segmentation, including region proposals, selective search, feature extraction, and bounding box refinement.
Mask RCNN Deep Learning Architectures4:24
Mask R-CNN extends faster r-cnn with a mask branch for pixel-level instance segmentation, using roi align for precise alignment and a regional proposal network.
Bonus Lecture: YOLOv8: Video and Image Object Detection with Python1:23

Setting-up Google Colab for Writing Python Code7:54
Set up and use Google Colab to write Python code with PyTorch, leveraging browser-based notebooks, GPU access, and seamless Google Drive integration for storing and sharing projects.
Connect Google Colab with Google Drive to Read and Write Data2:43
Learn to connect Google Colab with Google Drive to read and write data by mounting the Drive, granting access, and using Python code to access and save files from Colab.

Access Data from Google Drive to Colab Notebook2:44
Read images from Google Drive into a Colab notebook using Python, PIL, and pyplot to load from folder and display dog, cat, and pizza images for single and multi-label classification.
Data Preprocessing for Deep Learning Model5:00
Preprocess input images for deep learning by resizing to 256, center-cropping to 224, converting to tensor, and normalizing with training mean and std to match resnet and alexnet.

ResNet and AlexNet Models for Single-Label Image Classification8:03
Leverage pre-trained resnet and alexnet for single-label image classification on ImageNet data, using torchvision in Colab to predict and compare class scores.
Python Code for Single-Label Image Classification0:02
ResNet and AlexNet Models for Multi-Label Image Classification6:21
Learn multi-label image classification using ResNet and AlexNet in Python, switching from softmax to sigmoid to predict multiple items and top five labels.
Python Code for Multi-Label Image Classification0:02
Bonus Lecture: Deep Learning with Python for Image Classification0:44

Requirements

A Google Gmail account is required to get started with Google Colab to write Python Code
No programming experience required. You will learn everything you need to know

Description

Are you a beginner looking to embark on a journey into the fascinating world of Deep Learning and Artificial Intelligence (AI)? Look no further! Welcome to the world of deep learning, where cutting-edge technologies and incredible possibilities await! Our "Deep Learning & AI course with Python for Beginners" is your stepping stone into the captivating realm of artificial intelligence and machine learning. Whether you're a novice or have some programming experience, this course will empower you with the knowledge and skills to embark on a journey that is transforming industries worldwide. As industries increasingly adopt deep learning and AI technologies, the demand for skilled professionals is soaring. By completing this course, you'll position yourself at the forefront of one of the most dynamic and high-demand fields in tech. Unlock a world of opportunities, from AI research and data science to machine learning engineering and robotics.

Deep learning, a subset of artificial intelligence, has transcended its initial hype to become a transformative force across various fields. In healthcare, deep learning is revolutionizing disease diagnosis and treatment by analyzing medical images, such as MRIs and CT scans, with unprecedented accuracy. It is powering autonomous vehicles, enabling them to navigate complex environments safely. In finance, deep learning algorithms are used for fraud detection and stock market prediction. Natural language processing models, a part of deep learning, are behind voice assistants like Siri and chatbots that enhance customer service. Deep learning's applications extend to the entertainment industry, where recommendation systems personalize content, and to manufacturing, where it optimizes production processes. Whether in climate science, astronomy, or e-commerce, deep learning is reshaping the future by making sense of vast datasets and uncovering insights that were once unimaginable.

Course content:

Deep Learning and AI with Python Starting from Basic Concepts
Artificial Neurons - Building Blocks of Deep Learning and AI
Deep Convolutional Neural Networks (ResNet and AlexNet)
Learn UNet Deep Learning Architectur
Learn PSPNet Deep Learning Architecture
Learn PAN Deep Learning Architecture
Learn Region-Based Convolutional Neural Networks (RCNNs)
Setting-up Google Colab for Writing Python Code
Data Preprocessing using different Image Transformations with Python
Deep Learning Models to Perform Single and Multi-label Image Classification

This course is tailored for individuals with little to no prior experience in deep learning or Python programming. We'll start with the fundamentals and build your skills progressively. If you're a student aspiring to pursue a career in artificial intelligence or machine learning, this course will provide you with a strong foundation to kickstart your journey. If you're simply curious about the world of deep learning and want to explore its possibilities, this course is perfect for satisfying your intellectual curiosity.

Join us on this exciting journey and unlock the potential of Deep Learning and AI today! Enroll now to get started.

Who this course is for:

The course is designed for individuals who are new to the field of deep learning and wish to start their journey in this exciting area of artificial intelligence.
Whether you're a student in computer science, engineering, data science, or any related field, this course can supplement your academic knowledge and provide practical skills.

Deep Learning and AI with Python for Beginners

What you'll learn

Explore related topics

Course content

Introduction to Coruse1 lecture • 2min

Intro to Deep Learning and AI1 lecture • 14min

Deep Convolutional Neural Networks (ResNet and AlexNet)2 lectures • 6min

UNet Deep Learning Architecture1 lecture • 4min

PSPNet Deep Learning Architecture1 lecture • 5min

PAN Deep Learning Architecture2 lectures • 5min

Deep Region-Based Convolutional Neural Networks (RCNNs)3 lectures • 13min

Setting-up Google Colab for Writing Python Code2 lectures • 11min

Data Preprocessing with Python2 lectures • 8min

Deep Learning to Perform Image Classification with Python5 lectures • 15min

Requirements

Description

Who this course is for: