Search result for Building and training machine learning models Online Courses & Certifications
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Machine Learning Rapid Prototyping with IBM Watson Studio
by Mark J Grover , Meredith Mante- 4.6
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Approx. 9 hours to complete
This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. While it showcases the automated AI capabilies of IBM Watson Studio with AutoAI, the course does not explain Machine Learning or Data Science concepts. Machine Learning Algorithms Evaluation measures for models...
Custom and Distributed Training with TensorFlow
by Laurence Moroney , Eddy Shyu- 4.8
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Approx. 24 hours to complete
• Build your own custom training loops using GradientTape and TensorFlow Datasets to gain more flexibility and visibility with your model training. This Specialization is for early and mid-career software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models....
Using Machine Learning in Trading and Finance
by Jack Farmer , Ram Seshadri- 4
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Approx. 19 hours to complete
By the end of the course, you will be able to design basic quantitative trading strategies, build machine learning models using Keras and TensorFlow, build a pair trading strategy prediction model and back test it, and build a momentum-based trading model and back test it. Use Keras and Tensorflow to build machine learning models...
Deep learning for object detection using Tensorflow 2
by Nour Islam Mokhtari- 4.4
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9.5 hours on-demand video
Understand, train and evaluate Faster RCNN, SSD and YOLO v3 models using Tensorflow 2 and Google AI Platform This course is designed to make you proficient in training and evaluating deep learning based object detection models. After this, you will learn how to leverage the power of Tensorflow 2 to train and evaluate these models on your local machine....
$12.99
R: Neural Nets and CNN Architecture in R - Masterclass!
by Packt Publishing- 3.6
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6 hours on-demand video
The first course, Getting Started with Neural Nets in R, covers building and training neural network models to solve complex problems. This course covers an introduction to neural nets, the R language, and building neural nets from scratch- with R packages; specific worked models are applied to practical problems such as image recognition, pattern recognition, and recommender systems....
$11.99
Managing Machine Learning Projects with Google Cloud
by Google Cloud Training- 4.6
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Approx. 14 hours to complete
If you have questions about machine learning and want to understand how to use it, without the technical jargon, this course is for you. Learn how to translate business problems into machine learning use cases and vet them for feasibility and impact. Module 4: Building and evaluating ML models Building and evaluating ML models...
Customising your models with TensorFlow 2
by Dr Kevin Webster- 4.8
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Approx. 27 hours to complete
Welcome to this course on Customising your models with TensorFlow 2! In this course you will deepen your knowledge and skills with TensorFlow, in order to develop fully customised deep learning models and workflows for any application. Model subclassing and custom training loops Welcome to week 4 - Model subclassing and custom training loops...
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Reinforcement Learning for Trading Strategies
by Jack Farmer , Ram Seshadri- 3.7
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Approx. 12 hours to complete
In the final course from the Machine Learning for Trading specialization, you will be introduced to reinforcement learning (RL) and the benefits of using reinforcement learning in trading strategies. Introduction to Course and Reinforcement Learning Idiosyncrasies and challenges of data driven learning in electronic trading Understand the structure and techniques used in reinforcement learning (RL) strategies....
Machine Learning with Python, scikit-learn and TensorFlow
by Packt Publishing- 3.2
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9.5 hours on-demand video
Apply Machine Learning techniques to solve real-world problems with Python, scikit-learn and TensorFlow Explore popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks Yuxi (Hayden) Liu is currently an applied research scientist focused on developing machine learning models and systems for given learning tasks....
$12.99
AWS Computer Vision: Getting Started with GluonCV
by Thom LaneTop Instructor , Thomas DelteilTop Instructor , Soji AdeshinaTop Instructor- 4.6
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Approx. 31 hours to complete
The course discusses artificial neural networks and other deep learning concepts, then walks through how to combine neural network building blocks into complete computer vision models and train them efficiently. We will look at using pre-trained models for classification, detection and segmentation. Module 2: Machine Learning on AWS AWS Machine Learning Stack...
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