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Machine Learning is the hottest buzzword. But why is it that while fields such as Computer Vision or NLP have stellar achievements, the Cybersecurity industry staggers behind? Machine Learning is the hottest buzzword. Everybody loves it, everybody sells it. But why is it that while fields such as Computer Vision or Natural Language Processing have stellar achievements, with new record-breaking models published every other week, the Cybersecurity industry staggers behind? Are Anomaly Detection algorithms – so well beloved for the prevention of attacks and of fraud - really suitable for those intended purposes? What price do we pay for keeping things hushed? Where do our huge datasets fail us? And how, once we spot these issues, might we try and solve them? In this talk I will go over several points that hold us back, among them: our rapidly changing input data, and who’s to blame for it; the known issues of imbalanced & untagged datasets, and why our solutions for them are insufficient; and, finally, the biggest culprit: the confidential nature of our field, and how it keeps us from being great. The unspoken problems with Machine Learning in security: let’s talk about them.

Keynote recorded live at #datalift22 Summit Berlin 22.-24. Speaker: Noa Weiss, AI & Machine Learning Consultant Title: The Quick & Dirty AI Startup You just founded your AI startup - and now it’s time to build your algorithm. Join me to hear of simple ways to save R&D time without compromising on product quality, gathered from my experience consulting for multiple early-stage startups. If you’re thinking of starting your own startup, already have one, or are a sole data scientist in a brand-new venture - this talk is for you. Noa Weiss is an AI & machine learning consultant working with data for over a decade. She helps startups and larger companies use their data to drive business success. Noa leads the Israeli community of Women in Data Science, and is passionate about FemTech and promoting female entrepreneurship.

Machine Learning is the hottest buzzword. Everybody loves it, everybody sells it. But why is it that while fields such as Computer Vision or Natural Language Processing have stellar achievements, with new record-breaking models published every other week, the Cybersecurity industry staggers behind? Are Anomaly Detection algorithms – so well beloved for the prevention of attacks and of fraud - really suitable for those intended purposes? What price do we pay for keeping things hushed? Where do our huge datasets fail us? And how, once we spot these issues, might we try and solve them? In this talk I will go over several points that hold us back, among them: our rapidly changing input data, and who’s to blame for it; the known issues of imbalanced & untagged datasets, and why our solutions for them are insufficient; and, finally, the biggest culprit: the confidential nature of our field, and how it keeps us from being great. The unspoken problems with Machine Learning in security: let’s talk about them. Language - English Noa Weiss weissnoa.com Noa is an AI & machine learning consultant who’s been playing with data for over a decade, both in academia and in the tech industry. Prior to freelancing, Noa explored the world of risk & security, working for companies such as Armis and PayPal, as well as consulting startups on fraud prevention. In her spare time she leads the Israeli community of Women in Data Science, utilizes deep learning techniques to improve whale research at the Deep Voice foundation, and mentors junior data scientists taking their first steps in the field.

WIT Demystifying Data Science Conference 2020 Noa Weiss, Data Science & Machine Learning Consultant, about 10 Machine Learning Concepts Every Startup Founder Must Know. ⠀ Do you often find yourself in meetings with obscure machine learning terms thrown all around you, and no idea what they mean? There is hope yet. Designed for tech professionals, this talk introduces 10 must-know concepts in ML, giving you the basic tools to better understand the work around you. Rock the next water cooler chat with your newfound knowledge of these fundamentals of machine learning!

Details DataNights - Data Science Work in the Real World #5: Real-World Problems With Real-World Data ✔ ----------------------------------------------------------------------------------------------- Machine learning courses are all fun and games, but once you hit your first real job, new problems start rolling in. What to do if you don't have enough data? Who might listen to your plea for more "ground truth" labels? And what does this all have to do with a vacation in the tropics? Join Noa Weiss, an AI & Machine Learning consultant, to hear more about those real-world problems that come with real-world data, and how to tackle them like a pro.

https://www.greeninvoice.co.il/ Do you often find yourself in meetings with obscure machine learning terms thrown all around you, and no idea what they mean? There is hope yet. Designed for tech professionals unfamiliar with data science, this talk introduces 10 must-know concepts in ML, giving you the basic tools to better understand the work around you. Rock the next water cooler chat with your newfound knowledge of these fundamentals of machine learning. Noa Weiss is a data science & machine learning consultant who’s been playing with data for nearly a decade, both in academia and in the tech industry. Prior to freelancing, Noa explored the world of risk & security, working for companies such as Armis and PayPal, as well as consulting startups on fraud prevention. In her spare time she leads the Israeli community of Women in Data Science, and mentors junior data scientists taking their first steps in the field.

Noa is a freelance data scientist who’s been playing with data for nearly a decade. Prior to freelancing, Noa explored the world of risk & security, working for companies such as Armis and PayPal, as well as consulting startups on fraud prevention. She also leads the data science track of Open Knesset, a project to promote transparency in the Israeli parliament. In her spare time she leads the Israeli community of Women in Data Science, is active in the local LGBTQIA+ tech community, and mentors junior data scientists.

A talk from the 2016 international conference of the Society of Psychotherapy Research (SPR), presenting hierarchical linear modeling of the relationship between therapist interventions and the therapeutic alliance, with patient attachment style acting as a moderator.

מהם ההבדלים בין דאטה אנליסט, דאטה אנג'ניר ודאטה סיינטיסט? איך אפשר להגיע לתפקידים אלו בתעשייה? אילו כלים ומיומנויות נדרשים? הפודקאסט השלישי של הקהילה עונה בדיוק על זה (ועל עוד שאלות רבות נוספות!). הפודקאסט נערך בשיתוף עם קהילת Women in Data Science Israel. הדוברות בפודקאסט: נועה וייס - יועצת עצמאית לדאטה סיינס ומאשין לרנינג. היא עובדת עם דאטה כבר מעל לעשור, גם בתעשייה וגם באקדמיה, ומתמחה בתחומי הריסק ו-cybersecurity. כיום היא עוזרת לחברות גדולות וקטנות להשתמש בדאטה שלהן כדי לשפר ביצועים למקסם רווחים. בזמנה הפנוי היא מנהלת את הקהילה הישראלית של Women in Data Science, ופעילה בעמותת Deep Voice, שמשתמשת ביכולות דיפ לרנינג למחקר לוויתנים. בפרק הזה היא באה לספר לנו מה זה אומר להיות דאטה סיינטיסט. Noa Weiss ענת פולצ'ק - דאטא אנג'ניר בעלת תואר שני בדאטא סיינס. היא בעלת ניסיון של עשר שנים בתחום הדאטה מקצה לקצה: איסוף דאטה, בניית תשתיות ופייפליינים, ביצוע אנליזה ופיתוח דשבורדים, מחקר ובניית מודלים לחיזוי בתחום הרפואי. כיום מנהלת קבוצה של דאטא אנג'נירס בחברת wix.com, ובאה לספר לנו קצת על עולם הדאטא אנג'נירינג. Anat Polachek מורג שלו - דאטה אנליסטית בחברת מדיה מוכרת, בעלת תואר ראשון בהנדסת תעשייה וניהול עם התמחות במערכות מידע. בעלת ניסיון בניתוח דאטה, כריית דאטה, הפקת תובנות, בניית דשבורדים דינמיים ובעיקר אוהבת לספר את סיפורם של המספרים. כמו כן מנהלת הקהילה הטכנולוגית, Industry.net. Morag Shilo כמו כן אם עדיין לא נרשמתם כ - subscribers, מוזמנים! רשמים וקישורים רלוונטים לפודקאסט: (תודה לנועה וייס, כל הזכויות שמורות) הרצאת "10 מושגים שכדאי להכיר ב-Machine Learning" של נועה (בעברית): https://www.youtube.com/watch?v=iQDa2ShYvPc הרצאת "10 מושגים שכדאי להכיר ב-Machine Learning" של נועה (באנגלית): https://www.youtube.com/watch?v=thYknU_3zf4 פוסט של נועה על איך להשאר מעודכנ.ת בעולם הדאטה סיינס: https://towardsdatascience.com/data-science-street-smarts-navigating-the-sea-of-information-24091785fadb קהילת Women in Data Science בפייסבוק: https://www.facebook.com/groups/2032669270341585/ האתר של נועה: https://www.weissnoa.com/ קרדיט לג'נגל: עומר בונין שמעון