• JobLaunch : Data Analyst Study Group

    Online event

    ______

    Please note: this study group has been pushed forward by two weeks. Starting Tues the 12th of Oct.

    Please enrol in this study group by completing the Google Form below. We will notify you by email if you are accepted to take part in the group.

    https://forms.gle/nmMad4qbUtdZahNx7
    ________

    Want to learn the skills required to be a Data Analyst whilst simultaneously geting a job? We got you covered.

    In partnership with JobLaunch, DSAi is proud to announce our 8 week Data Analyst study sprint.

    Starting September the 14th, for 8 weeks every Tuesday & Wednesday from 6-8pm, we will be running through some of the best courses on the internet, with an industry expert teaching you Python, SQL, Data Visualisation & Communication skills. This is also a rare opportunity to learn from industry experts and build a network within the community, an absolute essential for any aspiring Data Analyst.

    Best of all this initiative is 100% free.

    ​​Attendees can expect to learn the following:

    👉 Learn to Program with Python:

    Fundamentals of Python programming including Variables, Expressions, Functions, Loops & Iteration, Data Structures, Object Orientated programming, Databases & Data Visualisation with Python

    👉 Data munging, scraping, sampling & cleaning with SQL:

    Where filters and ordering data, Group by aggregates, Summary statistics, Exploratory data analysis, Complex table joins, Entity relationship diagrams, SQL reverse engineering, Data problem solving techniques, Insert and load raw data & Table schemas and data types

    👉 Visualisation with Tableau & Communication Skills

    Create highly interactive Dashboards, Use trendlines to interrogate data, Perform Data Mining in Tableau, Implement Advanced Mapping Techniques, Create powerful storylines for presentation to Executives,

    ~

    Attendees will be expected to self-study for 10 to 15 hours each week before attending the group - this study group is not for the faint of heart.

    The best performing teams & individuals will have the option to choose between several Data Analyst job positions available both here in Sydney & abroad.

    We have professionals willing to assist throughout, an amazing sponsor and prizes lined up for the teams that produce the best work. More information will be emailed out to those who are successful in their application to the study group.

    For more information on this exciting opportunity please tune in our first event on the 12th of Oct.

    Best of luck & regards,

    The DSAi team

    6
  • JobLaunch : Data Analyst Study Group

    Online event

    ______

    Please note: this study group has been pushed forward by two weeks. Starting Tues the 28th of Sept.

    Please enrol in this study group by completing the Google Form below. We will notify you by email if you are accepted to take part in the group.

    https://forms.gle/nmMad4qbUtdZahNx7
    ________

    Want to learn the skills required to be a Data Analyst whilst simultaneously geting a job? We got you covered.

    In partnership with JobLaunch, DSAi is proud to announce our 8 week Data Analyst study sprint.

    Starting September the 14th, for 8 weeks every Tuesday & Wednesday from 6-8pm, we will be running through some of the best courses on the internet, with an industry expert teaching you Python, SQL, Data Visualisation & Communication skills. This is also a rare opportunity to learn from industry experts and build a network within the community, an absolute essential for any aspiring Data Analyst.

    Best of all this initiative is 100% free.

    ​​Attendees can expect to learn the following:

    👉 Learn to Program with Python:

    Fundamentals of Python programming including Variables, Expressions, Functions, Loops & Iteration, Data Structures, Object Orientated programming, Databases & Data Visualisation with Python

    👉 Data munging, scraping, sampling & cleaning with SQL:

    Where filters and ordering data, Group by aggregates, Summary statistics, Exploratory data analysis, Complex table joins, Entity relationship diagrams, SQL reverse engineering, Data problem solving techniques, Insert and load raw data & Table schemas and data types

    👉 Visualisation with Tableau & Communication Skills

    Create highly interactive Dashboards, Use trendlines to interrogate data, Perform Data Mining in Tableau, Implement Advanced Mapping Techniques, Create powerful storylines for presentation to Executives,

    ~

    Attendees will be expected to self-study for 10 to 15 hours each week before attending the group - this study group is not for the faint of heart.

    The best performing teams & individuals will have the option to choose between several Data Analyst job positions available both here in Sydney & abroad.

    We have professionals willing to assist throughout, an amazing sponsor and prizes lined up for the teams that produce the best work. More information will be emailed out to those who are successful in their application to the study group.

    For more information on this exciting opportunity please tune in our first event on the 14th of September.

    Best of luck & regards,

    The DSAi team

    9
  • DSAI: Quantitative Finance Special Edition

    Online event

    **THIS EVENT IS NOW ONLINE ONLY **

    Hear from quantitative finance leaders Girish Nair (Director, Global and Asia Pac Quantitative Strategist) of BofA Merrill Lynch and Berowne Hlavaty (Executive Director, Quantitative Equity Strategy) of J.P. Morgan as they discuss recent trends, insights and research highlights in the world of equity research.

    Berowne will focus on NLP (Natural Language Processing) and some state-of-the-art techniques in that space. Girish will provide a big picture view of some the new data products they’ve been working on.

    Coming along for this first in-person DSAi talk since prior to the Covid-19 pandemic.

    We will have Co-Presidents, Arturo Rodriguez and Mark Monfort as hosts along with other DSAi members.

    Timings as follows:

    6:00: to 6:10 – Welcome and intro (DSAi)

    6:10 to 6:25 – Speaker A

    6:25 to 6:30 – Questions

    6:30 to 6:45 – Speaker B

    6:45 to 6:50 - Questions

    The 10 minutes leftover cover any other questions that arise.

    7
  • SML: Machine Learning for Robotics Special Edition

    Online event

    NOTE 1: Woohoo! This is an IN-PERSON event! level 10, 11 York St.
    NOTE 2: DUE TO COVID SPACE IS LIMITED! If you would like to attend please complete the following Google Form - You will not be admitted otherwise:

    https://forms.gle/xW9ProqUHrbgFyDA8

    NOTE 3: ONLINE LINK:

    https://www.youtube.com/watch?v=VqMNZPBjyRo

    ~~~

    Over the last couple of years, machine learning has made huge strides in powering robotics. At the moment, this is largely through pick and place robots which use computer vision and pre-programmed motions, but around the corner are robots capable of dexterous manipulation that can learn any task which we can demonstrate to them.

    Sholto, Tristan & Tristan will present research that they are working on mentored by Google’s robotics team, who pioneered a way to teach complex manipulation through only hours of teleoperated ‘play’ data using self-supervised learning. They’ll talk about how they are trying to use language as a bridge between the robot’s own experiences and broader datasets of human interaction with the world so that the robot can both be instructed what to do in plain english - and learn to generalise beyond its own experiences. At the core of this is a combination of self-supervised and contrastive learning, which are the same family of methods driving the leaps in language and vision such as GPT-3 and CLIP/DALL-E by allowing us to extract richer signals from larger datasets.

    They’ll also talk about why robotic learning is so hard, where they see the next big advances in robotic learning and how they’ve gone about choosing directions for independent research.

    10
  • SML: Machine Learning Study Sprint!

    Needs a location

    Tired of starting an online course or a Machine Learning textbook and not being able to finish it?

    Tired of not being able to meet in person to form a study group?

    This group is for you.

    Starting on Thursday the 15th of October at 6pm, recurring for 4 weeks we are proud to present our SML “Study Sprint”.

    If you are currently working your way through an online course (or MOOC), a textbook, a youtube tutorial or other and would like to finish it with the support of others, use this group to ensure you stay on track.

    We are going to be using the best tools for learning at home known to humankind to keep you accountable & motivated to ensure you hit those Machine Learning study goals.

    We will be using the following tools to stay on track:

    Habitica - Gamifying your study goals. We will be turning your study goals into an RPG via Habitica to stay on track.

    Beeminder - The use of negative financial goals to stay accountable. This means a small financial commitment via Beeminder to ensure you hit your goals. If you miss your study goal, you loose money. Please see the comment directly below****

    HyperGraph - Next Generation note keeping tools. It is not enough to simply watch lectures, you need to process the information too. We will be using the HyperGraph note keeping app to do this.

    ***Note that in no way will SML be benefiting financially from this initiative. If you miss your goal, your money goes to Beeminder =D. Also, you get to choose by how much.

    We realise this is not for everyone & that the above might be asking a lot! We are looking for like minded people that are willing to commit to their goals and work through them together.

    In addition we will be kicking off the following:

    A Study Sprint Slack group. To form groups and help each other in real time.

    Weekly Zoom Meetings. Meeting every Thursday at 6pm via Zoom to report in & share our learnings with others.

    If you would like to be a part of this initiative, please sign up via the Google form below:

    https://forms.gle/51sp4H9qoRSM9h368

    Looking forward to kicking down some goals with you soon!

    The SML Team

    11
  • HoAi Podcast: Danny Ma on Data Science Mentorship.

    Needs a location

    In this episode of the Humans of Ai, We talk about Danny’s passion for mentorship and the challenges of finding the right mentor fit.

    Danny throws light on the current state of Data Science and Machine Learning and provides tips on how to improve yourself as a Data Scientist, the importance of working with and around data, along with the pros and cons of the Data Science field.

    Towards the end of the episode, Danny shares his views on the future of technology and the NEXT BIG THING in the field of Data Science.

    Find out more about Danny & his #DatawithDanny movement here:

    https://www.linkedin.com/in/datawithdanny/

    Podcast available via the links below:

    Direct in your browser:

    https://lnkd.in/gQvt4iB

    on iTunes here:

    https://lnkd.in/eByX-Dw

    On Spotify here:

    https://lnkd.in/enCBeXU

    On Sticher here:

    https://lnkd.in/gt4mves

  • SML Graph Machine Learning Special edition with Neo4j

    Online event

    NOTE: this is an online only event. Please join via the following Zoom link:

    https://zoom.us/j/2332523087
    ================

    In partnership with Neo4j, DSAi & SML is proud to present a Special Edition event focussing on the field of Graph Machine Learning & Graph Data Bases.

    This meetup will feature talks from two of Sydney’s industry experts in the field, Joshua Yu & Paul Conyngham.

    Joshua Yu’s presentation:
    ================

    Joshua will be presenting on the Connection Analysis for fake news and uncover the story behind Russian Twitter Trolls using Graph Machine Learning.

    During the 2016 U.S. election, Russian trolls infiltrated online conversations. NBC News sought to investigate and encountered two challenges: recovering deleted tweets and analysing the data to detect patterns. Reporters used Neo4j to scrutinize hundreds of thousands of tweets and expose tactics of Russian troll networks.

    So, what can social media platforms and governments do to monitor and prevent future abuse?

    First, it’s a matter of connections. In today’s hyper-connected world, it’s difficult to identify relationships in a dataset if you’re not using a technology purpose-built for storing connected data. It’s even more difficult if you’re not looking for connections in the first place.

    Second, once you’re storing and looking for connections within your datasets, it’s essential to detect and understand the patterns of behaviour reflected by those connections. In this case, a simple graph algorithm (PageRank) was able to illustrate that most of the Russian troll accounts behaved like single-minded bees with a focused job – and not like normal humans.

    Using a connections-first approach to analysing these sorts of datasets, both governments and social media platforms can more proactively detect and deter this sort of meddling behaviour before it has a chance to derail democracy or poison civil conversation.

    Paul Conyngham’s presentation:
    ================

    In this presentation, Paul Conyngham will present an Applied Machine Learning use case of Graph Machine Learning in his show case of “Identité” - a zero touch digital identity management & query system powered by Neo4j.

    We will walk through an example, where by Identité will be used in real time to create a digital profile to show how the power of Graph Machine learning & Graph Databases allows for auto discovery & assistance for similar firms looking to query unstructured data such as pdf, word files, emails, txt & even images to help build a defence case for a law firm.

    7
  • HoAi Podcast: Emre Kiciman & Amit Sharma - Causal Inference & Microsoft's DoWhy

    What is Causal Inference? Find out in this edition of the Humans of Ai Podcast👇:

    Emre Kiciman is the Senior Principal Researcher at Microsoft Research Ai in the Information and Data Sciences group, and Amit Sharma is a Senior Researcher at Microsoft Research India.

    In this episode of the Humans of Ai, we discuss how Emre and Amit started in the field of Science and Technology and then dive into how they got started in Causal Science. We further explore the concepts around Causal Inference, such as Causal Graphs and Confounding Variables. We then discuss Amit & Emre's new software library, “DoWhy – A Library for Causal Inference,” the motivation behind its creation and its significance.

    Towards the end of the episode, we talk about the advantages/disadvantages of Causal Inference and the ethical usage of bringing such sophisticated tools into Machine Learning.

    Podcast available via the links below:

    on iTunes here:

    https://lnkd.in/eByX-Dw

    On Spotify here:

    https://lnkd.in/enCBeXU

    On Sticher here:

    https://lnkd.in/gt4mves

  • SML: Sagemaker Workshop Special Edition via Zoom & Twitch

    Online event

    NOTE: this is an online only event. Please join via the following Zoom link:

    https://zoom.us/j/95992882299

    __________________________________________________________

    Description:

    This online workshop details the process one must undergo to build, train and deploy your models on Amazon SageMaker. We dive deep into the underlying APIs and demonstrate the code changes required to move your code from notebook to production. We also detail how niche SageMaker functionality can help you train your models faster, analyse and debug bad models, and proactively monitor their performance in production. Finally, we detail some cost optimisation tips for SageMaker, in addition to designing a simple automated pipeline for training and deploying your models.

    You can expect to learn:

    -How to orchestrate machine learning with Amazon SageMaker;
    -How to automate machine learning pipelines on AWS;
    -How SageMaker specific APIs for HPO, debugging, monitoring, etc can benefit you

    About the speaker- Angus Barnes:

    Angus is a Solutions Architect from Amazon Web Services that specialises in Machine Learning. He has a background in Mathematics and Software Engineering, and has held roles across a diverse set of fields, including; Web Development, DevOps, Cloud Architecture and Data Science. He has a keen interest in helping customers cost optimise, secure and orchestrate their ML workloads on AWS.

    2
  • The Humans of Ai Podcast: Damian Brady - The emerging field of MLops

    Needs a location

    What is MLOps? Find out in this edition of the Humans of Ai Podcast👇

    MLOps is the application of the best practises from DevOps - that is the tools & techniques that are required to take software & put it into production - and applying these same principles to the field of Data Science to formalise the process of training a machine learning model all the way through to putting the model into production.

    In this edition of the Humans of Ai, we interview Damian Brady - Senior Cloud DevOps Advocate at Microsoft & discuss how he got started in the field of Computer Science, then deep dive into Damian's field of expertise - MLops. Finally, we finish up the episode with what it is like to talk at a super conference - Microsoft Ignite.

    Podcast available via the links below:

    on iTunes here:

    https://lnkd.in/eByX-Dw

    On Spotify here:

    https://lnkd.in/enCBeXU

    On Sticher here:

    https://lnkd.in/gt4mves

    https://lnkd.in/gJ_ZkBG