• (paid) Workshop: Build AI applications from end to end with AWS and Sagemaker

    This is paid online workshop. You must register and pay at the link below. You can watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. AI Workshop: Build AI applications from end to end with AWS and Sagemaker Date/time: Aug 29th, 9am-12pm PT (US pacific time), check your local time. Registration: https://learn.xnextcon.com/course/coursedetails/C19082909 (you must pay and register at the website to receive the unique link to join the workshop). Format: online lectures + hands-on code labs Details: In this course you will learn how to train and deploy ML models in the Amazon Web Services (AWS) Cloud. This includes how to use Amazon S3 to store your data, AWS Sagemaker to train ML models, how to deploy these models as a REST Endpoint, and how to use Amazon Lambda serverless features to connect these models to an external URL to use with your applications. We will also test out the REST endpoint using a Python application. For this exercise we will use an example of Bank Churn (predicting whether a bank customer is likely to leave the bank). We will provide sample datasets and python programs to run with this use case. This workshop is fun and exciting and will show you how to use Cloud AI services to not just train your models but also how to deploy them and use them in real life for your smart applications. You can use these techniques to add ML to your development projects, add ML to your applications, or to build new applications. Topics covered: *AI Cloud services overview, focusing on using AWS Cloud *Full model lifecycle - how to train your model, deploy it, and connect it to an application *A business use case - Bank Churn *Dataset preparation and feature engineering *Model training with several ML techniques for Classification (KNN, Linear Learner, XGBoost and Factorization Machines) *Model evaluation metrics (Accuracy) *Model deployment as a REST endpoint *How to use your model predictions inside a Python application, deploy and test

  • AI webinar: Auto Data Visualization and Machine Learning, by Google Engineer

    This is online live tech talk. You will join online using zoom.us (video conference tool), and watch, follow, Q&A with speakers from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. AI webinar: Auto Data Visualization and Machine Learning, by Google Engineer Start date/time: Aug 16th, 10am-11am PT (US pacific time), check your local time. Registration: https://learn.xnextcon.com/event/eventdetails/W19081610 (you must register at the website to receive the unique link to join the webinar). Details: Data Scientists today grapple with two problems: 1. Big Data 2. Bewildering Choice. Big Data enables data scientists to analyze more of what is available, but they cannot visualize it or explain it so easily. In addition, there is a bewildering array of tools available which means substantial work with steep learning curves to master each one of them. The solution is automation: automate what is mundane so we can focus on the most important. Here I will describe what is available in terms of Open Source and Proprietary tools for automating Data Science tasks and introduce 2 new tools: one to visualize any sized data set with one click, another: to try multiple ML models and techniques with a single call. I will provide the Github Repos for both for free in the talk. Make sure to register at: https://learn.xnextcon.com/event/eventdetails/W19081610 after you sign up and enroll to this webinar, you will receive an unique link to join online.

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  • AI webinar: Explainability and Bias in AI

    Needs a location

    This is online live tech talk. You will join online using zoom.us (video conference tool), and watch, follow, Q&A with speakers from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. AI webinar: Explainability and Bias in AI Start date/time: Aug 9th, 10am-11am PT (US pacific time), check your local time. Registration: https://learn.xnextcon.com/event/eventdetails/W19080910 (you must register at the website to receive the link to join the workshop online). Details: There is a growing need both for machine learning models that are explainable and models that are fair and free from bias. In this two-part talk, we will present an introduction to explainability and bias in machine learning. In the first part, we will start with an overview of techniques, such as LIME and SHAP, for explaining machine learning models. In addition to helping us explain models and their predictions, explainability methods can also help us debug and find flaws in our models. In the second part of the talk, we will then go over some of the state-of-the-art methods for detecting and mitigating bias, and talk briefly about general challenges in handling bias. Make sure to register at: https://learn.xnextcon.com/event/eventdetails/W19080910 after you sign up and enroll to this webinar, you will receive an unique link to join online.

  • (paid) AI workshop: machine learning with code series 3

    This is online live workshop. You will join online using zoom.us (video conference tool), and watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. AI workshop: machine learning with code series 3 Start date/time: Aug 8th, 11am-1pm PT (US pacific time), check your local time. Registration: https://learn.xnextcon.com/course/coursedetails/C19080811 (you must register at the website to receive the link to join the workshop online). Details: The best way to learn machine learning is by coding. We start the series of workshops to learn machine learning by writing code in python. Students will follow instructors to implement machine learning algorithms, models, simple applications from scratch through hands on coding labs. And learn about the real word application of different machine learning models with explanation of the necessary principles behind it. The aim of this workshop is to simplify the inherent concepts of Machine Learning and learn hands-on through building python code and understand applications of the algorithms. In the 3rd of series, we will learn the following three algorithms: *Gradient boosting *PCA Make sure to register at: https://learn.xnextcon.com/course/coursedetails/C19080811 after you sign up and enroll to this workshop, you will receive an unique link to join the workshop online.

  • Using Apache Cassandra and Kafka to Scale Next Gen Apps

    General Assembly Boston

    Adoption of open source software (OSS) at the enterprise level has flourished, as more businesses discover the considerable advantages that open source solutions hold over their proprietary counterparts, and as the enterprise mentality around open source continues to shift. Join us as we dive into how to identify good application candidates for Apache Cassandra and Kafka as well as best practices and common pitfalls. This presentation will also cover: The origins of Apache Cassandra and Kafka and how these technologies have come to shape how next-gen applications are built. Production use cases of Cassandra and Kafka: Real-time payments and buying a house (Lendi and Worldpay) Core concepts that make the magic; Explaining the technical attributes that make your project a good fit for these technologies and the architectural patterns that make the best use of it’s capability. Speaker: Ben Bromhead, CTO, Instaclustr Ben is responsible for working closely with his engineering team and customers to build highly available, scalable applications for Instaclustr, the world's only multi-cloud, self-service Cassandra as a Service (CaaS) provider. RSVP: https://www.eventbrite.com/e/big-data-boston-using-apache-cassandra-and-kafka-to-scale-next-gen-apps-tickets-64677498138 Due to building security, registration is required for entry to this event. Snacks and refreshments will be provided. See you there!

  • AI NEXTCon Conference NYC 2019

    New York

    AI NEXTCon Developers Conference NYC 7/23-26, 2019. Best price (starting just at $99) is available for limited time. Register on eventbrite: https://ainyc19.eventbrite.com Join us the 8th AI NEXTCon, the leading AI tech conference hosted around the world. AI NEXTCon brings together top technical engineers, practitioners, influential technologists and data scientists to share solutions and practical experiences in computer vision, speech, NLP, machine learning, deep learning, data science/analytics. The conference features a blend of hands-on workshops, inspirational keynotes, deep dive tech talks, and networking opportunity with like minded colleagues. it's 4 days conference with 50+ tech speakers/tech talk sessions, 50+ tech talks, and 5+ workshop/code labs. Speakers are mainly from engineering teams from Microsoft Amazon Uber Airbnb Pinterest Google Facebook Twitter Linkedin, Nvidia, Intel, etc... AI NEXTCon is one of premium tech events specially geared to tech engineers, developers, data scientists, and machine learning engineers, has attracted more than 500 tech lead speakers, 6000+ tech engineers attending and more than 30 sponsors (like Microsoft, Amazon, Uber, Oracle, eBay, OfferUp, Google, IBM, AI2, Zillow, Alibaba, Huawei, DiDi, LinkedIn, OmniSci, and more). Website: http://ainyc19.xnextcon.com Date: Main Conference: 7/23-24th, 2019 (Tue and Wed) Hands-on Workshop: 7/25-26th, 2019 (Thu and Fri) Tracks: The conference features thoughtful tech leaders keynote in the morning and breakout tracks tech talks in the afternoon: *Computer Vision *Speech&NLP *Machine Learning *Deep Learning *Data Science & Analytics AICamp: Online AI learning platform with talks, courses, bootcamps: https://learn.xnextcon.com AI NEXTCon (Seattle, NYC, San Francisco and Beijing): http://www.xnextcon.com Twitter: @atiglobalorg

  • AI webinar: An Introduction to Neural Architecture Search

    AI webinar: An Introduction to Neural Architecture Search This is online webinar. You can watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. Start date/time: 7/19, 10am PT (US pacific time). check your local time. Registration: https://learn.xnextcon.com/event/eventdetails/W19071910 Details: Deep learning has seen an explosion of interest since 2012, and since then, deep networks have gotten more complicated and more specialized. How do researchers know which neural network to use for a given dataset? Neural Architecture Search (NAS), which is a subset of hyperparameter optimization, is the process of automating the search to find the best neural architecture for a given dataset. In this webinar, we will give a survey of the NAS literature, including details for some of the most popular techniques such as reinforcement learning and Bayesian optimization.

  • AI webinar: Build and integrate AI features into applications

    This is online webinar. You can watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. Free AI webinar: Build and integrate AI features into applications Start date/time: 7/16, 10am PT (US pacific time). check your local time. Registration: https://learn.xnextcon.com/event/eventdetails/W19071610 Details: In this workshop we show how to build effective AI services for your applications. We will run through several use cases of numerical and text analysis data - from the beginning of raw data to a fully deployed and managed AI service in the cloud - with all the steps in between (data preparation, feature engineering, model training, model validation, deployment, application integration and monitoring). You will also learn how to assess whether AI is helping your business application and how to manage and tune your new AI feature over time. We will use AWS as the base for our exercises. All datasets are public and will be provided for the participants access.

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  • AI webinar: NLP - Streaming Sentiment Analysis of Live Events

    This is online webinar. You can watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. Free AI webinar: NLP - Streaming Sentiment Analysis of Live Events Start date/time: 7/11, 10am PT (US pacific time). check your local time. Registration: https://learn.xnextcon.com/event/eventdetails/W19071110 Details: In this talk, I will talk through the architecture and analysis of a streaming sentiment analysis pipeline used to analyze the Twitter stream during live events like the Game of Thrones Series Finale and the NBA Finals. Topics covered will include Kubernetes for resilient applications, VADER sentiment analysis, Apache Beam and Google Cloud Dataflow streaming processing, and analysis of results.

  • (paid) AI workshop: machine learning with code series 2

    Needs a location

    This is online live workshop. You will join online using zoom.us (video conference tool), and watch, follow, Q&A with instructors from anywhere around the world. Miss the live session due to time zone or conflict? you can learn session replay at any time afterwards. AI workshop: machine learning with code series 2 Start date/time: 7/10, 9am-12pm PT (US pacific time). Registration: https://learn.xnextcon.com/course/coursedetails/C19071009 Details: The best way to learn machine learning is by coding. We start the series of workshops to learn machine learning by writing code in python. Students will follow instructors to implement machine learning algorithms, models, simple applications from scratch through hands on coding labs. And learn about the real word application of different machine learning models with explanation of the necessary principles behind it. The aim of this workshop is to simplify the inherent concepts of Machine Learning and learn hands-on through building python code and understand applications of the algorithms. In the second of series, we will learn the following three algorithms: *Logistic regression *Support Vector Machine *Random forest