• Telling Human Stories With Data

    Needs a location

    We want to invite you to participate in the FREE ODSC Webinar! Date: September 4th Time: 11 am - 12 pm BST To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/5174684751357268493 Robust data analysis underpins every business decision, public sector project and non-profit initiative. But data in its raw form often fails to convince crucial lay audiences – either due to its complexity, or due to suspicion and mistrust. And you can’t help guide the world in the right direction if you alienate key decision-makers or the public. This talk, delivered by journalist and data visualization specialist Alan Rutter, will cover an audience-centered approach to visualizing data. It will introduce tried-and-tested techniques for communicating data-driven stories effectively to people from a broad range of backgrounds, and deal with some of the common problems that practitioners encounter. Alan Rutter is the founder of consultancy Fire Plus Algebra, and is a specialist in communicating complex subjects through data visualisation, writing and design. He has worked as a journalist, product owner and trainer for brands and organisations including Guardian Masterclasses, WIRED, Time Out,the Home Office, the Biotechnology and Biological Sciences Research Council and Liverpool School of Tropical Medicine. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/

  • Telling Human Stories With Data

    Skills Matter

    Please be advised that pre-registration is REQUIRED. Registration link: https://skillsmatter.com/meetups/12578-telling-human-stories-with-data Speaker: Alan Rutter, Founder of consultancy Fire Plus Algebra https://www.linkedin.com/in/alanjrutter/ Topic: Telling Human Stories With Data Schedule: 6:30pm - 7:00pm - ODSC Intro, Pizza & Refreshments 7:00pm - 7:50pm - Talk 7:50pm - 8:00pm - Q&A 8:00pm - 8:30pm - Networking Bio: Alan Rutter is the founder of consultancy Fire Plus Algebra, and is a specialist in communicating complex subjects through data visualization, writing and design. He has worked as a journalist, product owner and trainer for brands and organizations including Guardian Masterclasses, WIRED, Time Out, the Home Office, the Biotechnology and Biological Sciences Research Council and Liverpool School of Tropical Medicine. Abstract: Robust data analysis underpins every business decision, public sector project and non-profit initiative. But data in its raw form often fails to convince crucial lay audiences – either due to its complexity, or due to suspicion and mistrust. And you can’t help guide the world in the right direction if you alienate key decision-makers or the public. This talk, delivered by journalist and data visualization specialist Alan Rutter, will cover an audience-centered approach to visualizing data. It will introduce tried-and-tested techniques for communicating data-driven stories effectively to people from a broad range of backgrounds, and deal with some of the common problems that practitioners encounter. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • West Conference Oct 29 - Nov 1: https://odsc.com/california • Europe Conference Nov 19 - 22: https://odsc.com/london

  • Drinks with Data Scientists

    The Fellow

    Join our Drinks with Data Scientists! Enjoy this great opportunity to exchange information on challenges, experiences and goals with fellow Data Scientists. That will be an amazing networking time together. Starting at 7 pm Place: The Fellow - 24 York Way, London N1 9AA (Kings Cross tube station) Invite your friends, or come by yourself and make new ones! • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • India Conference Aug 7 - 10: https://india.odsc.com/ • West Conference Oct 29 - Nov 1: https://odsc.com/california • Europe Conference Nov 19 - 22: https://odsc.com/london

  • A machine that predicts the global economy in real-time

    Please be advised that pre-registration is REQUIRED. Registration link: https://skillsmatter.com/meetups/12535-odsc-july-predicting-the-global-economy-in-real-time Speaker: Dr. Darko Matovski, CEO of causaLens https://www.linkedin.com/in/matovski/ Topic: A machine that predicts the global economy in real-time Schedule: 6:30pm - 7:00pm - ODSC Intro, Pizza & Refreshments 7:00pm - 7:50pm - Talk 7:50pm - 8:00pm - Q&A 8:00pm - 8:30pm - Networking Bio: Dr. Darko Matovski is the CEO of causaLens. The company builds a machine that predicts the global economy in real-time and serves prominent organizations including hedge funds and asset managers. Darko has also worked for cutting edge hedge funds and research institutions. For example, the National Physical Laboratory in London (where Alan Turing worked) and Man Group in London. Darko has a Ph.D. in Machine Learning and an MBA. Abstract: By 2020, there will be 50 billion devices measuring the heartbeat of the global economy in real-time. Measurements about the economic activity are primarily represented in the form of time-series data. Other types of data such as text, images, voice, video, etc. get transformed into the form of time-series. Until now, economic researchers have used structural and econometric models for time-series predictions. The performance of these models has been underwhelming. Modern algorithms, such as machine learning and new sources of data have demonstrated strong potential. However, the current machine learning techniques require weeks or months of human expert's time, work only on static datasets and are unable to adapt to unseen changes taking place in the real world. In this talk, we will demonstrate how AutoML for time-series predictions has the ability to build more sophisticated predictive models in a fraction of the time (and cost) while adapting to a dynamic world. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • West Conference Oct 29 - Nov 1: https://odsc.com/california • Europe Conference Nov 19 - 22: https://odsc.com/london

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  • Natural Language Processing with TensorFlow

    Skills Matter

    Please be advised that pre-registration is REQUIRED. Registration link: https://skillsmatter.com/meetups/12326-odsc-april-meetup-natural-language-processing-with-tensorflow?admin_preview=true Speaker: Barbara Fusinska - Machine Learning Strategic Cloud Engineer at Google https://www.linkedin.com/in/barbarafusinska/ Workshop Topic: Natural Language Processing with TensorFlow Schedule: 6:30pm - 7:00pm - ODSC Intro, Pizza & Refreshments 7:00pm - 7:50pm - Talk 7:50pm - 8:00pm - Q&A 8:00pm - 8:30pm - Networking Bio: Barbara is a Strategic Cloud Engineer at Google with a strong software development background. While working with a variety of different companies, she gained experience in building diverse software systems. This experience brought her focus to the Data Science and Machine Learning field. She believes in the importance of the data and metrics when growing a successful business. Alongside collaborating around data architectures, Barbara still enjoys programming activities. Currently speaking at conferences in-between working in London. Tweets at @BasiaFusinska and blogs on http://barbarafusinska.com. Abstract: Natural Language Processing offers a variety of techniques to get insight from and generate text data. Going beyond simple representations and taking advantage of Deep Learning and RNNs, the models can use document context to perform more accurately. With the help of libraries like TensorFlow, building neural networks and applying NLP is now available to the wider audience. In this tutorial, Barbara will make the introduction to NLP concepts and deep learning architectures. The audience will be walked through two labs: sentiment analysis and text generation. After this session, the audience will have a good understanding of the deep learning concepts when it comes to NLP. The attendees will create a classifying model that takes advantage of the document context using TensorFlow library and scale their solutions using Google Cloud ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 3: https://odsc.com/boston • Europe Conference Nov 19 - 22: https://odsc.com/london

  • ODSC East 2019 Warm-Up Webinar

    Needs a location

    02/20/2019 ODSC East 2019 Warm-Up ODSC East is getting closer! We want to invite you to participate in ODSC East's Warm-Up webinar. This event will feature four 30 minutes tutorials presented by our distinguished speakers listed below. These sessions will highlight some of the most integral topics, tools, and languages in AI for Engineers and give attendees a preview of what can be expected at ODSC East, Boston's largest applied data science conference. This four-day conference will feature over 250+ speakers and 300+ hours of content. To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/2996766616681683971 Date: Feb.20th, 2019 Time: 1 pm - 3 pm EST Full Agenda Detail: Session 1 - Programming with Data: Python and Pandas (30 Minutes) Speaker: Daniel Gerlanc, President, Enplus Advisors Inc. In this workshop, you will learn how to accelerate your data analyses using the Python language and Pandas, a library specifically designed for interactive data analysis. Pandas is a massive library, so we will focus on its core functionality, specifically, loading, filtering, grouping, and transforming data. Having completed this workshop, you will understand the fundamentals of Pandas, be aware of common pitfalls, and be ready to perform your own analyses. Session 2 - Real-ish Time Predictive Analytics with Spark Structured Streaming (30 Minutes) Speaker: Scott Haines, Principal Software Engineer, Twilio In this workshop, we will dive deep into what it takes to build and deliver an always-on "real-ish time" predictive analytics pipeline with Spark Structured Streaming. The core focus of the workshop material will be on how to solve a common complex problem in which we have no labeled data in an unbounded timeseries dataset and need to understand the substructure of said chaos in order to apply common supervised and statistical modeling techniques to our data in a streaming fashion. Session 3 - Modern and Old Reinforcement Learning (30 Minutes) Speaker: Leonardo De Marchi, Head of Data Science and Analytics, Badoo Reinforcement Learning recently progressed greatly in the industry as one of the best techniques for sequential decision making and control policies. In this workshop we will explore Reinforcement Learning, starting from its fundamentals and ending creating our own algorithms. We will use OpenAI gym to try our RL algorithms. In particular, we will start with some popular techniques like Multi Armed Bandit, going thought Markov Decision Processes and Dynamic Programming. We then will also explore other RL frameworks and more complex concepts like Policy gradients methods and Deep Reinforcement learning, which recently changed the field of Reinforcement Learning. In particular we will see Actor Critic models and Proximal Policy Optimizations that allowed openai to beat some of the best Dota players. We will also provide the necessary Deep Learning concepts for the course. Session 4 - (30 Minutes) Speaker: Sourav Dey, Ph.D., CTO, and Alex NG, Ph.D., Senior Data Engineer, Manifold (co-presenters) In this workshop, Sourav and Alex will focus heavily on the DevOps side of things, demonstrating how to use Orbyter to spin up data science containers and discussing experiment management as part of the Lean AI process. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 3: https://odsc.com/boston

  • Happy Hour with Data Scientists

    The Argyle

    Join our Happy Hour with Data Scientists! Enjoy this great opportunity to exchange information on challenges, experiences and goals with fellow Data Scientists. That will be an amazing networking time together. Starting at 7pm Place: The Argyle - 1 Greville St, London EC1N 8PQ Nearest station is Farringdon Invite your friends, or come by yourself and make new ones! • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 4: https://odsc.com/boston

  • ODSC East 2019 Warm-Up Webinar

    Needs a location

    ODSC East is getting closer! We want to invite you to participate in ODSC East's Warm-Up webinar. This event will feature four 30 minutes tutorials presented by our distinguished speakers listed below. These sessions will highlight some of the most integral topics, tools, and languages in Deep Learning and Machine Learning and give attendees a preview of what can be expected at ODSC East, Boston's largest applied data science conference. To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/7482285874203395331 Date: Jan 24th, 2019 Time: 1 - 3 pm EST Full Agenda Detail: Session 1 - Becoming The Complete Data Scientist with Data Literacy and Data Storytelling (30 Minutes) Speaker: Dr.Kirk Borne, Principal Data Scientist Abstract: I will review some of the key data literacy components that contribute to successful data science in real world applications. In discussing these concepts, I will give examples through the art of data storytelling, which aims to answer the core questions that your clients, colleagues, and stakeholders want to have answered: What? So what? Now what? Your technical skills may bring you customers, but it's not the technical stuff that you know (i.e., your successes) that brings your customers back. What brings customers back is your customers' successes, which are nurtured and grown through clear explanations of the data, the modeling activities, and the results, which they can then share with others. Session 2 - Introduction to Machine Learning (30 Minutes) Speaker: Andreas Mueller, Ph.D., Author, Lecturer, Core Contributor of scikit-learn Abstract: Machine learning has become an indispensable tool across many areas of research and commercial applications. This talk will give a general introduction to machine learning, as well as introduce practical tools for you to apply machine learning in your research. We will focus on one particularly important subfield of machine learning, supervised learning. The goal of supervised learning is to "learn" a function that maps inputs x to an output y, by using a collection of training data consisting of input-output pairs. We will walk through formalizing a problem as a supervised machine learning problem, creating the necessary training data and applying and evaluating a machine learning algorithm. The talk should give you all the necessary background to start using machine learning yourself. Session 3 - Pre-trained models, Transfer Learning and Advanced Keras Features (30 Minutes) Speaker: Francesco Mosconi, Ph.D. in Physics and Data Scientist at Catalit LLC, Instructor at Udemy Abstract: You have been using keras for deep learning models and are ready to bring your skills to the next level. In this workshop, we will explore the use of pre-trained networks for image classification, transfer learning to adapt a pre-trained network to your use case, multi gpu training, data augmentation, keras callbacks and support for different kernels. Session 4 - Easy Visualizations for Deep Learning (30 Minutes) Speaker: Douglas Blank, Senior Software Engineer at Comet.ML Abstract: Visualizations are important in order to debug and understand how a Deep Learning model is representing a problem. In this talk, I will introduce a layer of software (ConX) that was developed on top of Keras in Jupyter Notebooks for making useful (and beautiful) visualizations of activations of a neural network. We will develop a model from scratch, train it, test it, and explore various tools for visualizing learning over time in representational space. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 3: https://odsc.com/boston

  • Tuning the untunable: Lessons for tuning expensive deep learning functions

    We want to invite you to participate in ODSC Webinar! During this webinar, Patrick Hayes, CTO & Co-Founder of SigOpt, walks through a variety of methods for training models with lengthier training cycles before diving deep on this multitask optimization functionality. The rest of the talk will focus on how this type of method works and explain the ways in which deep learning experts are deploying it today. Finally, we will talk through the implications of early findings in this area of research and next steps for exploring this functionality further. This is a particularly valuable and interesting talk for anyone who is working with large data sets or complex deep learning models. To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/7311596589281404161 Date: Jan 10th Time: 07 pm - 09 pm GMT Agenda Detail: Session: Tuning the untunable: Lessons for tuning expensive deep learning functions Speaker: Patrick Hayes Abstract: Tuning models with lengthy training cycles, typically found in deep learning, can be extremely expensive to train and tune. In certain instances, this high cost may even render tuning infeasible for a particular model. Even if tuning is feasible, it is often extremely expensive. Popular methods for tuning these types of models, such as evolutionary algorithms, typically require several orders of magnitude the time and compute as other methods. And techniques like parallelism often come with a degradation of performance trade-off that results in the use of many more expensive computational resources. This leaves most teams with few good options for tuning particular expensive deep learning functions. But new methods related to task sampling in the tuning process create the chance for teams to dramatically lower the cost of tuning these models. This method referred to as multitask optimization, combines “strong anytime performance” from bandit-based methods with “strong eventual performance” of Bayesian optimization. As a result, this process can unlock tuning for some deep learning models that have particularly lengthy training and tuning cycles. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 3: https://odsc.com/boston

  • Data Science for Good Webinar

    Needs a location

    We want to invite you to participate in ODSC Data Science for Good Webinar! We will discuss how can we leverage data science and its versatile tools to solve real-life problems. Technologies progress and develop, data becomes more prolific and useful. How can we, as data scientists benefiting from this momentum, help the rest of the world catch up? To access this webinar, please register using the link below: https://attendee.gotowebinar.com/register/560915152644257027 We are bringing 4 speakers to present 30 minutes sessions. Date: Dec 19th Time: 2 - 4 pm EST (11 am - 13pm PT) Agenda Detail: Session 1 - Data wrangling to provide solar energy access across Africa (30 Minutes) Speaker: Brianna Schuyler, Ph.D. Abstract: More than 600 million people in Sub-Saharan Africa have no access to electricity, and no documented financial history. A family can light their home and keep necessary electronics (such as a cell phone) charged using a small solar panel and battery, but most solar devices are not affordable to a vast number of people making $2 a day or less. One solution to this problem is offering solar energy kits on a Pay As You Go basis, providing financial loans to families until they are able to pay off the cost of their device. However, people with severely restricted income oftentimes exhibit sporadic payment behavior which poses an interesting prediction problem. This rich and unique dataset can be used to develop credit profiles for individuals, allowing them access to credit for other life-changing loans or utilities. In addition to financial information, the solar devices themselves send millions of bits of information regularly using a GSM chip. Information transferred through GSM, along with the financial data amassed through loan repayment, provide a fascinating dataset on which to model and explore. Data analysis and machine learning techniques allow increased energy access to those for whom the costs of solar were previously prohibitive, as well as increased adoption of renewable energy sources in a rapidly growing population. Session 2 - Detecting semantic bias through interpretability (30 Minutes) Speaker: Eric Schles Abstract: In this session, we will juxtapose classical statistical interpretability techniques against cutting-edge techniques. We will show how these newer techniques allow us to interpret models like neural networks, ensembles and support vector machines. The two main new tools we will use are SHAP and LIME. We will apply this to data synthetic datasets, showing how one could detect semantic bias (non-statistical bias). Session 3 - AI Ethics: Current Challenges Speaker: Abhishek Gupta Abstract: This talk will highlight some of the emerging challenges when it comes to the responsible and ethical development and deployment of AI. It will use recent examples to illustrate some of the challenges and present potential strategies on how to best mitigate these issues. The talk will also highlight 2 projects coming up from the Montreal AI Ethics Institute that are aiming to concretely address some of these challenges. ODSC Links: • Get free access to more talks like this at LearnAI: https://learnai.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI/ • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science/ • East Conference Apr 30 - May 3: https://odsc.com/boston