Deep Learning and Neural Networks with Python Zero to Expert

Deep Learning with Python for Classification, Semantic and Instance Segmentation, Pose Estimation, and Object Detection


What you'll learn
Deep Learning with Python and Pytorch Complete Guide
Machine Learning to Deep Learning Paradigm Shift Key Concepts
Artificial Deep Neural Networks Coding from Scratch in Python
Deep Convolutional Neural Networks Coding from Scratch in Python
Transfer Learning with Deep Pretrained Models using Python
Deep Learning for Image Classification with Python
Deep Learning for Pose Estimation with Python
Deep Learning for Instance Segmentation with Python
Deep Learning for Semantic Segmentation with Python
Deep Learning for Object Detection with Python
Train, Test and Deploy Deep Learning Models for Real-world Applications
Calculate Performance Metrics (Accuracy, Precision, Recall, IOU) with Python



Requirements
You will learn everything you need to know starting from Deep Learning with Python basics to advanced.
A Google Gmail account to get started with Google Colab to write Python Code

Description
Unlock the power of artificial intelligence with our comprehensive course, "Deep Learning with Python ." This course is designed to transform your understanding of machine learning and take you on a journey into the world of deep learning. Whether you're a beginner or an experienced programmer, this course will equip you with the essential skills and knowledge to build, train, and deploy deep learning models using Python and PyTorch. Deep learning is the driving force behind groundbreaking advancements in generative AI, robotics, natural language processing, image recognition, and artificial intelligence. By enrolling in this course, you’ll gain practical knowledge and hands-on experience in applying Python skills to deep learning
Course Outline
Introduction to Deep Learning
Understanding the paradigm shift from machine learning to deep learning
Key concepts of deep learning
Setting up the Python environment for deep learning
Artificial Deep Neural Networks: Coding from Scratch in Python
Fundamentals of artificial neural networks
Building and training neural networks from scratch
Implementing forward and backward propagation
Optimizing neural networks with gradient descent
Deep Convolutional Neural Networks: Coding from Scratch in Python
Introduction to convolutional neural networks (CNNs)
Building and training CNNs from scratch
Understanding convolutional layers, pooling, and activation functions
Applying CNNs to image data
Transfer Learning with Deep Pretrained Models using Python
Concept of transfer learning and its benefits
Using pretrained models for new tasks
Fine-tuning and adapting pretrained models
Practical applications of transfer learning
Deep Learning for Image Classification with Python
Techniques for image classification
Building image classification models
Evaluating and improving model performance
Deploying image classification models
Deep Learning for Pose Estimation with Python
Introduction to pose estimation
Building and training pose estimation models
Using deep learning for human pose estimation
Deep Learning for Instance Segmentation with Python
Understanding instance segmentation
Building and training instance segmentation models
Techniques for segmenting individual objects in images
Deep Learning for Semantic Segmentation with Python
Fundamentals of semantic segmentation
Building and training semantic segmentation models
Techniques for segmenting images into meaningful parts
Real-world applications of Semantic segmentation
Deep Learning for Object Detection with Python
Introduction to object detection
Building and training object detection models
Techniques for detecting and localizing objects in images
Practical use cases and deployment
Who Should Enroll?
Beginners
: Individuals with basic programming knowledge who are eager to dive into deep learning.
Intermediate Learners
: Those who have some experience with machine learning and wish to advance their skills in deep learning and PyTorch.
Professionals
: Data scientists, AI researchers, and software engineers looking to enhance their expertise in deep learning and apply it to real-world problems.
What You'll Gain
A solid foundation in deep learning concepts and techniques
Hands-on experience in building and training various deep learning models from scratch
Proficiency in using Python and PyTorch for deep learning applications
The ability to implement and fine-tune advanced models for image classification, pose estimation, segmentation, and object detection
Practical knowledge to deploy deep learning models in real-world scenarios
Why Choose This Course?
Comprehensive Content
: Covers a wide range of deep learning topics and applications.
Hands-on Projects
: Practical coding exercises and real-world projects to solidify your understanding.
Expert Guidance
: Learn from experienced instructors with deep expertise in deep learning and Python.
Flexible Learning
: Access the course materials anytime, anywhere, and learn at your own pace.
Enroll now and embark on your journey to mastering deep learning with Python and PyTorch. Transform your skills and open up new career opportunities in the exciting field of artificial intelligence!
See you inside the course!!
Who this course is for:
This course is designed for AI enthusiasts looking to build a solid foundation in Deep Learning with Python.
Data Scientists, Computer Vision Engineers, Software Engineers, and AI researchers seeking to enhance their expertise in Deep Learning.

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