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 learningCourse OutlineIntroduction to Deep Learning Understanding the paradigm shift from machine learning to deep learningKey concepts of deep learningSetting up the Python environment for deep learningArtificial Deep Neural Networks: Coding from Scratch in PythonFundamentals of artificial neural networksBuilding and training neural networks from scratchImplementing forward and backward propagationOptimizing neural networks with gradient descentDeep Convolutional Neural Networks: Coding from Scratch in PythonIntroduction to convolutional neural networks (CNNs)Building and training CNNs from scratchUnderstanding convolutional layers, pooling, and activation functionsApplying CNNs to image dataTransfer Learning with Deep Pretrained Models using PythonConcept of transfer learning and its benefitsUsing pretrained models for new tasksFine-tuning and adapting pretrained modelsPractical applications of transfer learningDeep Learning for Image Classification with PythonTechniques for image classificationBuilding image classification modelsEvaluating and improving model performanceDeploying image classification modelsDeep Learning for Pose Estimation with PythonIntroduction to pose estimationBuilding and training pose estimation modelsUsing deep learning for human pose estimationDeep Learning for Instance Segmentation with PythonUnderstanding instance segmentationBuilding and training instance segmentation modelsTechniques for segmenting individual objects in imagesDeep Learning for Semantic Segmentation with PythonFundamentals of semantic segmentationBuilding and training semantic segmentation modelsTechniques for segmenting images into meaningful partsReal-world applications of Semantic segmentationDeep Learning for Object Detection with PythonIntroduction to object detectionBuilding and training object detection modelsTechniques for detecting and localizing objects in imagesPractical use cases and deploymentWho 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 GainA solid foundation in deep learning concepts and techniquesHands-on experience in building and training various deep learning models from scratchProficiency in using Python and PyTorch for deep learning applicationsThe ability to implement and fine-tune advanced models for image classification, pose estimation, segmentation, and object detectionPractical knowledge to deploy deep learning models in real-world scenariosWhy 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.
Homepage

https://www.udemy.com/course/deep-learning-and-neural-networks-with-python/