Deep Learning Specialization
The Deep Learning Specialization equips you with the skills to build and optimize neural networks using Python and TensorFlow. It covers architectures like CNNs, RNNs, LSTMs, and Transformers, allowing learners to apply these skills to real-world AI cases.
TensorFlow Developer Professional Certificate
This course teaches how to build and train neural networks using TensorFlow through a hands-on program. It helps you gain skills to create AI-powered applications, prepare for the Google TensorFlow Certificate exam, and apply your knowledge to real-world projects.
Introduction to Deep Learning & Neural Networks with Keras
This course introduces deep learning and compares it to artificial neural networks. It covers various models, teaching unsupervised models like autoencoders and restricted Boltzmann machines and supervised models like CNNs and recurrent networks.
TensorFlow 2 for Deep Learning Specialization
This specialization allows machine learning researchers and practitioners to develop practical TensorFlow skills. It covers building, training, and evaluating models, customizing workflows with TensorFlow’s lower-level APIs, and developing probabilistic models using the TensorFlow Probability library.
NYU Deep Learning
This course covers deep learning history, neural networks, gradient descent, and backpropagation. It includes practical implementations using PyTorch, covering ConvNets, RNNs, autoencoders, GANs, transformers, and graph neural networks.
Intro to Deep Learning with PyTorch
This course teaches deep learning basics and how to build neural networks using PyTorch. Learners work on practical projects like image classification, style transfer, and text generation. The syllabus includes neural networks, CNNs, RNNs, and deploying models.
Practical Deep Learning For Coders
This course covers how to set up a GPU server and create deep learning models for computer vision, NLP, and recommendation systems. It includes CNNs, RNNs, and their practical applications.
Probabilistic Deep Learning with TensorFlow 2
This course delves into the probabilistic aspect of deep learning using TensorFlow. It focuses on handling uncertainty in real-world datasets and teaches how to develop probabilistic models with TensorFlow Probability.
Machine Learning with Python: From Linear Models to Deep Learning
This course teaches machine learning principles and algorithms for making predictions from training data. It covers topics like representation, over-fitting, regularization, clustering, classification, reinforcement learning, SVMs, and neural networks.
Deep Learning Applications for Computer Vision
This course teaches Computer Vision, starting with classic approaches and then applying Deep Learning methods to the same problems. It explores modern machine learning tools covering topics like image classification, object detection, segmentation, facial recognition, and pose estimation.
We make a small profit from purchases made via referral/affiliate links attached to each course mentioned in the above list.
If you want to suggest any course that we missed from this list, then please email us at asif@marktechpost.com
The post Top Deep Learning Courses To Try In 2024 appeared on MarkTechPost.
If you want to evolve your company with AI, stay competitive, use for your advantage Top Deep Learning Courses To Try In 2024.
Discover how AI can redefine your way of work. Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI. Define KPIs: Ensure your AI endeavors have measurable impacts on business outcomes. Select an AI Solution: Choose tools that align with your needs and provide customization. Implement Gradually: Start with a pilot, gather data, and expand AI usage judiciously.
For AI KPI management advice, connect with us at hello@itinai.com. And for continuous insights into leveraging AI, stay tuned on our Telegram t.me/itinainews or Twitter @itinaicom.
Spotlight on a Practical AI Solution:
Consider the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.
Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com.
