Case Study


Deep Learning and AI Success Stories - insideBIGDATA

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We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. The complete insideBIGDATA Guide to Deep Learning & Artificial Intelligence is available for download from the insideBIGDATA White Paper Library. We also explained the difference between AI, machine learning and deep learning, and examined the intersection of AI and HPC. The complete insideBIGDATA Guide to Deep Learning & Artificial Intelligence is available for download from the insideBIGDATA White Paper Library, courtesy of NVIDIA.


Azure-Readiness/hol-azure-machine-learning

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This content is designed for audience without any prior Machine learning knowledge. It starts from very basics and goes to advanced topics. We will try to keep this content live and include more and more advanced lab sessions with real life scenarious. Thanks for your support and feedback to make this content better.


Analytics training courses

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Metrics to measure model performance. Metrics to measure model performance. Logistic regression case study on churn modeling. Case study on using decision trees to predict churn.


Automated Machine Learning -- A Paradigm Shift That Accelerates Data Scientist Productivity @ Airbnb

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A fair amount of our data science projects involve machine learning, and many parts of this workflow are repetitive. Model Diagnostics: Learning curves, partial dependence plots, feature importances, ROC and other diagnostics are extremely useful to generate automatically. AML is a powerful set of techniques for faster data exploration as well as improving model accuracy through model tuning and better diagnostics. The above case study highlights AML's capability to improve model accuracy, however we have realized AMLs other benefits as well.


Apache Spark MLlib 2.x: Productionize your Machine Learning Models

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Apache Spark has rapidly become a key tool for data scientists to explore, understand and transform massive datasets and to build and train advanced machine learning models. How do I embed what I have learned into customer facing data applications? In this latest Data Science Central webinar, we will discuss: Best practices on how customers productionize machine learning models Case studies with actual customers Live tutorials of a few example architectures and code in Python, Scala, Java and SQL Speaker: Richard Garris, Principal Solutions Architect -- Databricks Inc. Hosted by: Bill Vorhies, Editorial Director -- Data Science Central


Machine Learning: Regression Coursera

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About this course: Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions.


Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp: Peter Norvig: 9781558601918: Amazon.com: Books

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First, the good: This book is a great read, both the code and non-code sections. Unless you are using Lisp as your programming language (I'm using Haskell), section 3 (optimizing your Lisp code Logic programming) will be hit and miss too. So, to sum up: If you want to learn Lisp, Norvig recommends Paul Graham's book. If you want to learn AI, Norvig has written AI: A Modern Approach.


Artificial intelligence use cases/application areas in B2B sales appliedAI

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Sales content personalization and analytics: Sales reps serve customers better with sales content personalized to individual customers. Predictive inside sales platforms score customers' likelihood of converting based on 3rd party and company data, allowing your sales reps to prioritize effectively Sales rep next action suggestions: AI will analyze your sales reps actions and leads will be analyzed to suggest the next best action. Customer sales contact analytics: Analyze all customer contacts including phone calls or emails to understand what behaviors and actions drive sales. To get more information about these use cases including references, case studies, customer videos and information on vendors operating in this space, please visit us at appliedAI.com.


Machine Learning, NLP and Network Analysis-Guided Medical Research : A Case Study

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Some of the most relevant candidate Medical Topics were found to be the following shown Table 1 (list is not inclusive): 1) Sulfation 2) Bile Acid Homeostasis 3) Vitamin K Metabolism 3) Carboxylation 4) Urea Cycle 5) Adrenal Insufficiency Note that Topics listed in Table 1 (and in subsequent posts of this Blog) may also be associated with each other (e.g. However by looking at the scaled importance on the example chart, this particular algorithm suggests that cysteine desulfurase, cysteine dioxygenase and -generally speaking- Medical Topics associated with Carboxylation,Sulfation and Cysteine Metabolism appear to be relevant to our Research subject. Based on results from a particular type of Network Analysis and output from several Machine Learning Algorithms, it is hypothesized that Vitamin K - related Genes play a central role to the Syndromes discussed in this post (and possibly more syndromes having similar symptoms): Suspected Genes are any combination of the following Genes that are either directly or indirectly associated with Vitamin K. These are: "It is known that MERTK/TAM deficient animals show signs of autoimmunity with features resembling certain human autoimmune pathologies including serum autoantobodies against DNA, collagen and antiphospholipid antibodies (e.g anticardiolipin antibodies) and lymphocyte activation and hyperproliferation" [1] Note also that anticardiolipin antibodies have been found to patients of CFS [2] Apart from MERTK, VKORC1 is important for Protein Disulfide Bond formation within the Endoplasmic Reticulum [3] Note also that Vitamin K needs Bile Salts for proper absorption: [1] - p. 268. Suspected Genes are any combination of the following Genes that are either directly or indirectly associated with Vitamin K. "It is known that MERTK/TAM deficient animals show signs of autoimmunity with features resembling certain human autoimmune pathologies including serum autoantobodies against DNA, collagen and antiphospholipid antibodies (e.g anticardiolipin antibodies) and lymphocyte activation and hyperproliferation" [1] Note also that anticardiolipin antibodies have been found to patients of CFS [2] Apart from MERTK, VKORC1 is important for Protein Disulfide Bond formation within the Endoplasmic Reticulum [3] Note also that Vitamin K needs Bile Salts for proper absorption: [1] - p. 268.


Machine Learning - Stanford University Coursera

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In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.