​PCA vs TSNE — El Clásico

🔗 PCA vs TSNE — El Clásico
PCA vs TSNE — the match which excites us all

Variational Temporal Abstraction

Taesup Kim, Sungjin Ahn, Yoshua Bengio

https://arxiv.org/pdf/1910.00775.pdf

#ActiveLearning #ArtificialIntelligence #DeepLearning

​Python - A Perfect Language for Developing Future-Proof Application

🔗 Python - A Perfect Language for Developing Future-Proof Application
Let’s Talk About Future Proof Mobile Apps Security.

​Create fake but meaningful data using {fakir}

🔗 Create fake but meaningful data using {fakir}
One of the problems in data science is finding the right set of dataset for the right set of problem you want to teach/learn/experiment…

​Introduction to Sequence Modeling Problems

🔗 Introduction to Sequence Modeling Problems
Task of predicting what word comes next?

🎥 Lecture #6: Support Vector Machine 10/30/2019 Wed
👁 1 раз ⏳ 5399 сек.
Lecture #6: Support Vector Machine
CIS 419/519 2019C Applied Machine Learning on 10/30/2019 Wed

​What is Hebbian Learning?

🔗 What is Hebbian Learning?
The simplest neural network (threshold neuron) lacks the capability of learning, which is its major drawback. In the book “The…

​Как устроен гибридный игровой ИИ и в чём его преимущества
В продолжение некогда поднятой в нашем блоге темы игрового искусственного интеллекта поговорим о том, насколько применимо к нему машинное обучение и в каком виде. Своим опытом и выбранными на его основе решениями поделился эксперт по вопросам ИИ в Apex Game Tools Якоб Расмуссен.

В последние годы ведётся много разговоров о том, что машинное обучение кардинально изменит игровую индустрию, ведь эта технология уже стала прорывной во многих других цифровых приложениях. Но не стоит забывать, что игры устроены намного сложнее, чем симулятор вождения автомобиля, программа управления дроном или алгоритмы распознавания лиц на изображении.

🔗 Как устроен гибридный игровой ИИ и в чём его преимущества
В продолжение некогда поднятой в нашем блоге темы игрового искусственного интеллекта поговорим о том, насколько применимо к нему машинное обучение и в каком вид...

​Discerning Odors Using Machine Learning

🔗 Discerning Odors Using Machine Learning
Hey Google, what does this smell like?

🎥 Тимофей Черноусов || Машинное обучение в продакшн
👁 1 раз ⏳ 966 сек.
Конференция DataFest Siberia 2019

​Recommendation System Series Part 2: The 10 Categories of Deep Recommendation Systems That Academic

🔗 Recommendation System Series Part 2: The 10 Categories of Deep Recommendation Systems That Academic
The 10 Categories of Deep Recommendation Systems That Academic Researchers Should Pay Attention To

🎥 Schol-AR
👁 4 раз ⏳ 94 сек.
Schol-AR is Augmented Reality for Scientific Communication.

Go here to download and try the App:
http://ini.stg.ini.usc.edu/ScholAR/download.html

Data in this video is featured from:

Liew, S.-L. et al. A large, open source dataset of stroke anatomical brain images and manual lesion segmentations. Scientific Data 5, 180011 (2018).

Bienkowski, M. S. et al. Integration of gene expression and brain-wide connectivity reveals the multiscale organization of mouse hippocampal networks. Nat Neurosci 21, 1628–1

​Real time face recognition with CPU

🔗 Real time face recognition with CPU
After reading this article, you will understand how to use MobileFaceNet to build a real-time face recognition system with CPU.

​A Few Pragmatic Arguments in Favor of Decentralized Artificial Intelligence

🔗 A Few Pragmatic Arguments in Favor of Decentralized Artificial Intelligence
Modern artificial intelligence is experiencing many challenges related to its increased centralization.

​The Perfect Formula for FinTech Products: CX = ML + UX

🔗 The Perfect Formula for FinTech Products: CX = ML + UX
When the FinTech industry was just coming of age, most companies launched with one simple offering: a mobile wallet, debit card, or spare…

🎥 Deep learning with Apache MXNet
👁 1 раз ⏳ 1454 сек.
Learn more about AWS at - https://amzn.to/2q5hVw7.
MXNet is a fully-featured, flexibly-programmable, and ultra-scalable deep learning framework supporting state of the art deep learning models. It provides both low-level control and high-level APIs that allow developers to mix imperative and symbolic programming models and to code in their language of choice (including Python, Scala, Java, C++, and R). Besides its computational and memory efficiency, MXNet is lightweight and portable and can run on various

🎥 TensorFlow World 2019 Keynote
👁 1 раз ⏳ 4601 сек.
O'Reilly and TensorFlow are teaming up to present the first TensorFlow World. It brings together the growing TensorFlow community to learn from each other and explore new ideas, techniques, and approaches in deep and machine learning.

0:02 - Opening keynote by Jeff Dean
25:40 - The latest from TensorFlow by Megan Kacholia
37:41 - TensorFlow, open source, and IBM by Frederick Reiss
42:55 - Accelerating ML at Twitter by Theodore Summe
53:22 - Enterprise-ready TensorFlow in the Cloud by Craig Wiley
1:03:25 -

​Loading Reddit posts using AWS Lambda and CloudWatch events

🔗 Loading Reddit posts using AWS Lambda and CloudWatch events
Last month I finished a 12 weeks data science bootcamp at General Assembly where we did a lot of awesome projects using Machine Learning…

​Use the Isolated Forest with PyOD!

🔗 Use the Isolated Forest with PyOD!
If you were asked to separate the above trees till all are isolated, which tree will be the easiest? You might say the most left one since…

​NoTraffic, No Problems: AI Startup Improves Intersections | NVIDIA Blog

🔗 NoTraffic, No Problems: AI Startup Improves Intersections | NVIDIA Blog
Israel-based company NoTraffic is using AI to transform intersections into intelligent decision makers, cutting delays and carbon emissions.