Machine Learning Models used in Facebook

machine learning models at facebook

This post quickly represents machine learning projects and related machine learning models. The above diagram represents the usage of the following learning algorithms: Support Vector Machines (SVM) Gradient-boosted decision trees Multi-layer Perceptron (MLP): Used for ranking and personalizing news feeds, ads, search etc. Convolutional neural networks (CNN): Recurrent neural networks (RNN): Used for language translation, speech recognition, content understanding References

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13 Programming Languages used for Machine Learning

Programming languages used for machine learning

In this post, you will learn about different programming languages which can be used to create (train) machine learning models to solve supervised and unsupervised learning problems. Here are the top 13 programming languages used for machine learning: R Language: R is one of the most popular programming language and environment for statistical computing and graphics. Python: There are some of the following Python libraries which makes it easy to create machine learning/deep learning models: Scikit-learn library (Classical machine learning models): Packages such as NumPy, SciPy, Pandas are very useful and helpful in creating supervised and unsupervised learning models. Deep learning models using python libraries provided by Tensorflow, PyTorch, Theanos, CNTK, …

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Top 5 Machine Learning Introduction Slides for Beginners

Machine learning neural network slides

In this post, you will get to know a list of introduction slides (ppt) for machine learning. These slides could help you understand different types of machine learning algorithms with detailed examples. One or more slides from the following list could be used for making presentations on machine learning. If you are looking out for topics to be included in the machine learning course for your internal training purpose in your organization, the details presented below might turn out to be very helpful. If you are starting on learning data science, these could be good slides. Machine Learning Overview Machine Learning: An Overview: The slides present introduction to machine learning …

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Andrew NG Machine Learning Coursera Videos

In this post, you will get to know the list of Andrew NG Machine Learning Coursera Videos. Here is the information: Youtube playlist of machine learning videos which are same as that of Andrew NG machine learning course on Coursera. One could use Internet Download Manager (IDM) to download these videos. Use Coursera-dl script found on Github to download the machine learning course. The script makes it easier to batch download lecture resources (e.g., videos, ppt, etc) for Coursera classes. Given one or more class names and account credentials, it obtains week and class names from the lectures page, and then downloads the related materials into appropriately named files and directories. Use AcademicTorrents website …

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MIT OCW Machine Learning Courses Information

MIT Opencourseware Machine Learning

In this post, you get the information related to MIT OCW machine learning course from MIT OpencourseWare (OCW). They use  Matlab as the primary programming environment. The documentation for Matlab could be found on this page, Matlab Documentation.  The course is provided by Electrical Engineering and Computer Science department. Other related courses which could be useful for data scientist / machine learning engineers are some of the following: Introduction to probability (Video lectures, Lecture notes) Introduction to computational thinking and data science (Video lectures, Lecture notes) Lecture Notes – Machine Learning Course Lecture notes could be found on the following topics: Introduction, linear classification, perceptron update rule (PDF) Perceptron convergence, generalization (PDF) …

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Machine Learning – Insurance Applications Use Cases

machine learning insurance applications use cases

In this post, you will learn about some of the following insurance applications use cases where machine learning or AI-powered solution can be applied: Insurance advice to consumers and agents Claims processing Fraud protection Risk management AI-powered Insurance Advice to Consumers & Agents Insurance Advice to Consumers: Machine learning models could be trained to recommend the tailor made products based on the learning of the consumer profiles and related attributes such as queries etc from the past data. Such models could be integrated with Chatbots (Google Dialog flow, Amazon Lex etc) applications to create intelligent digital agents (Bots/apps) which could understand the intent of the user, collect appropriate data from the user (using prompts) …

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AWS reInvent – Top 7 New Machine Learning Services

Amazon Forecast Technology Architecture

In this post, you will learn about some great new and updated machine learning services which have been launched at AWS re:Invent Conference Nov 2018. My personal favorite is Amazon Textract. Amazon Personalize Amazon Forecast Amazon Textract Amazon DeepRacer Amazon Elastic inference AWS Inferentia Updated Amazon Sagemaker Amazon Personalize for Personalized Recommendations Amazon Personalize is a managed machine learning service by Amazon with the primary goal to democratize recommendation system benefitting smaller and larger companies to quickly get up and running with the recommendation system thereby creating the great user experience. Here is the link to Amazon Personalize Developer Guide. The following are some of the highlights: Helps personalize the user experience using some of …

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Solution – Macbook Air Stuck at Progress Bar Loading

mac air stuck progress bar loading

In this post, you will learn about the solution related to Mac Air Stuck at Progress Bar Loading. The reason I am doing this post is that my Mac Air had been showing the same behavior for the last several months and I was able to finally fix it. I am hoping that the solution does help someone. Anyways, in the whole process, I started my Mac Air several times in voice-over mode and became expert at it. Commands/Solutions which didn’t work I contacted Apple customer service two times and they said that it looks to be a software problem after I tried all the steps they suggested. I was asked to …

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Guidelines for Creating an Ethical AI Framework

Ethical AI Framework Components

In this post, you will learn about how to create an Ethical AI Framework which could be used in your organization. In case, you are looking for Ethical AI RAG Matrix created with Excel, please drop me a message. The following are key aspects of ethical AI which should be considered for creating the framework: Fairness Accountability Transparency Reliability & Safety Data privacy and security Fairness AI/ML-powered solutions should be designed, developed and used in respect of fundamental human rights and in accordance with the fairness principle. The model design considerations should include the impact on not only the individuals but also the collective impact on groups and on society at large. The following represents some …

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GitFlow Workflow Best Practices & Quiz Questions

Gitflow Workflow - Master, Release, Develop, Feature

In this post, you will learn about some of the best practices in relation to managing your development and production releases using GitFlow Workflow. There will be a master branch which is called as an official repository. Forking a develop branch of the master: To start with, we will fork off another branch of the master which we may call as “develop”. This branch will act as an integration branch for features branches. NOTE: feature in features branches does not represent the features in machine learning. “Develop” branch will act as a parent to the feature branches. This means that developers would fork from “develop” branch and their changes are merged back into “develop” branch. In real-world scenarios, …

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Javascript Security Vulnerabilities Examples (DarwinBox)

In this post, you will learn quick tips on security vulnerabilities related to Javascript based on analysis of how Javascript assets are managed in DarwinBox, and how to fix those security vulnerabilities. Security Vulnerabilities found with Javascript Assets While assessing the Javascript assets of DarwinBox, the following was found: Coding: Javascript code could be easily read and understood. There is a need to minimize and uglify the code. Method naming: The name of methods leak the implementation details and the underlying technology used. This could be used by hackers for planning attacks. For example, the method such as “doElasticSearch”. This represents that ElasticSearch is used for the search. File naming: The name of files represented …

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Angular Bootstrap Hello World App – Sample Code

In this post, you will learn about how to get your Angular App to use Bootstrap CSS and Javascript libraries for creating some great UI. The following are the steps for creating the Angular app with Bootstrap CSS and Javascript: Get started by creating a Hello World App. Check out the post, Angular 7 Hello World App for greater details. Go to the folder consisting of index.html. This is the folder src within the project folder. Place the following code within the head tag. The code primarily represents the Bootstrap CSS file and a viewport meta tag for responsive pages. Place the following code within the body tag. The code represents Javascript libraries of JQuery and Bootstrap. Test the Angular …

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Ethical AI Principles – IBM, Google, Intel, Microsoft

microsoft ethical ai principles

In this post, you will get a quick glimpse of ethical AI principles of companies such as IBM, Intel, Google, and Microsoft. The following represents the ethical AI principles of companies mentioned above: IBM Ethical AI Principles: The following represents six ethical AI principles of IBM: Accountability: AI designers and developers are responsible for considering AI design, development, decision processes, and outcomes. Value alignment: AI should be designed to align with the norms and values of your user group in mind. Explainability: AI should be designed for humans to easily perceive, detect, and understand its decision process, and the predictions/recommendations. This is also, at times, referred to as interpretability of AI. Simply …

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IEEE Bookmarks on Ethical AI Considerations

ethical ai design ieee

In this post, you will get to have bookmarks for ethical AI by IEEE (Institute of Electrical and Electronics Engineers) group. Those starting on the journey of ethical AI would find these bookmarks very useful. ML researchers and data scientists would also want to learn about ethical AI practices to apply them while building and testing the models. The following are some bookmarks on ethical AI considerations by IEEE group: The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems: An initiative by IEEE for setting up new standards and solutions, certifications and codes of conduct, and consensus building for ethical implementation of intelligent technologies to ensure that these technologies are …

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AI-powered Project Baseline to Map Human Health

project baseline

In this post, you will learn about technologies and data gathering strategy for Project Baseline, an initiative by Google. Project Baseline is an IOT-based AI-powered initiative to map human health. Different kinds of machine learning algorithms including deep learning etc would be used to understand different aspects of human health and make predictions for overall health improvements and precautionary measures. This would require a very large volume of data to be gathered and processed before being fed into AI models. The following represents the data gathering strategies for Project Baseline: Diagnostic tests covering blood-related tests; specialized tests such as ECG, chest X-ray, eyesight check Doctor examination leading to the collection of data related to health …

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Machine Learning Models – Bias Mitigation Strategies

Machine learning models - Bias mitigation strategies

In this post, you will learn about some of the bias mitigation strategies which could be applied in ML Model Development lifecycle (MDLC) to achieve discrimination-aware machine learning models. The primary objective is to achieve a higher accuracy model while ensuring that the models are lesser discriminant in relation to sensitive/protected attributes. In simple words, the output of the classifier should not correlate with protected or sensitive attributes. Building such ML models becomes the multi-objective optimization problem. The quality of the classifier is measured by its accuracy and the discrimination it makes on the basis of sensitive attributes; the more accurate, the better, and the less discriminant (based on sensitive attributes), the better. The following are some of …

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