Search result for Theory of deep learning Online Courses & Certifications
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Deep Learning by TensorFlow 2.0 Basic to Advance with Python
by Shiv Onkar Deepak Kumar- 3.3
17.5 hours on-demand video
Become Deep Learning professional by learning from Deep Learning professional As a practitioner of Deep Learning, I am trying to bring many relevant topics under one umbrella in the following topics. Foundation of Deep Learning TensorFlow 2. Best practices for Deep Learning and Award-winning Architectures Foundation of Deep Learning TensorFlow 2....
$12.99
Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications
by Kimberly Karalekas- 0.0
Approx. 5 hours to complete
The course looks at computer vision neural network models from a variety of popular machine learning frameworks and covers writing a portable application capable of deploying inference on a range of compute devices. Intermediate Intel® Distribution of OpenVINO™ toolkit for Deep Learning Applications Implementation Examples: Batch of Images Implementation Examples: Stream of Images...
Natural Language Processing with Sequence Models
by Younes Bensouda Mourri , Łukasz Kaiser , Eddy Shyu- 4.5
Approx. 22 hours to complete
In Course 3 of the Natural Language Processing Specialization, offered by deeplearning. If you’d like to prepare additionally, you can take Course 1: Neural Networks and Deep Learning of the Deep Learning Specialization. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization....
Introduction to Trading, Machine Learning & GCP
by Jack Farmer , Ram Seshadri- 4
Approx. 9 hours to complete
In this course, you’ll learn about the fundamentals of trading, including the concept of trend, returns, stop-loss, and volatility. By the end of the course, you will be able to use Google Cloud Platform to build basic machine learning models in Jupyter Notebooks. Applications of ML in the Real World Introduction to Neural Networks and Deep Learning...
AI Workflow: Machine Learning, Visual Recognition and NLP
by Mark J Grover , Ray Lopez, Ph.D.- 4.5
Approx. 14 hours to complete
Explain the use of linear and logistic regression in supervised learning applications Explain the use of tree-based algorithms in supervised learning applications Explain the use of Neural Networks in supervised learning applications Discuss the major variants of neural networks and recent advances Create and test an instance of Watson Visual Recognition Building Machine Learning and Deep Learning Models...
Deep Learning in Computer Vision
by Anton Konushin , Alexey Artemov- 3.8
Approx. 13 hours to complete
Deep learning added a huge boost to the already rapidly developing field of computer vision. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. Deep learning in optical flow estimation Deep learning models for image segmentation...
Intro to TensorFlow for Deep Learning
by Magnus Hyttsten , Juan Delgado , Paige Bailey- 0.0
Approx. 2 months
Learn how to build deep learning applications with TensorFlow. You'll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models. By the end of this course, you'll have all the skills necessary to start creating your own AI applications. Developed by Google and Udacity, this course teaches a practical approach to deep learning for software developers....
Free
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Introduction to Applied Machine Learning
by Anna Koop- 4.7
Approx. 7 hours to complete
By the end of the course, you will be able to clearly define a machine learning problem using two approaches. This is the first course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute. The Three Kinds of Machine Learning Deep Learning for Identifying Metastatic Breast Cancer (advanced supplemental)...
Unsupervised Deep Learning in Python
by Lazy Programmer Team- 4.5
8.5 hours on-demand video
Autoencoders, Restricted Boltzmann Machines, Deep Neural Networks, t-SNE and PCA This course is the next logical step in my deep learning, data science, and machine learning series. Since this course is the 4th in the deep learning series, I will assume you already know calculus, linear algebra, and Python coding. Understand how stacked autoencoders are used in deep learning...
$34.99
Applied AI with DeepLearning
by Romeo Kienzler , Niketan Pansare , Tom Hanlon , Max Pumperla , Ilja Rasin- 4.4
Approx. 24 hours to complete
This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. Introduction to deep learning...