hoaphumanoid

5 ms·

1.
New release of Microsoft Recommenders: new algorithms, notebooks and utilities(github.com)
2 points by hoaphumanoid 7y ago|0 comments
2.
Building recommender systems with Azure ML service: best practices on deployment(azure.microsoft.com)
3 points by hoaphumanoid 7y ago|1 comments
3.
by hoaphumanoid 8y ago
thanks for the comment, would this definition be clearer: "Recall at k is the proportion of relevant items found in the top-k recommendations"?
4.
by hoaphumanoid 8y ago
hey one of the authors here. We are planning to create some notebooks on recommendation about recommendation algos :-)
5.
Top 35 AI solutions for today's key industries(miguelgfierro.com)
2 points by hoaphumanoid 8y ago|0 comments
6.
A Gentle Explanation of Dimensionality Reduction with T-SNE(miguelgfierro.com)
2 points by hoaphumanoid 8y ago|0 comments
7.
Evidence-Based Software Design(miguelgfierro.com)
2 points by hoaphumanoid 8y ago|0 comments
8.
Python Pro Tips: Understanding Explicit Is Better Than Implicit(miguelgfierro.com)
1 points by hoaphumanoid 8y ago|0 comments
9.
Introduction to Fraud Detection Systems(kdnuggets.com)
1 points by hoaphumanoid 8y ago|0 comments
10.
Real-Time Fraud Detection(miguelgfierro.com)
2 points by hoaphumanoid 8y ago|0 comments
11.
A Beginner's Guide to Python Testing(miguelgfierro.com)
3 points by hoaphumanoid 8y ago|0 comments
12.
Demystifying WebSockets for Real-Time Web Communication(miguelgfierro.com)
3 points by hoaphumanoid 8y ago|0 comments
13.
Top Mistakes and Learnings from My Startup: Postmortem Samsamia(miguelgfierro.com)
184 points by hoaphumanoid 8y ago|71 comments
14.
10 Ethical Issues of Artificial Intelligence and Robotics(miguelgfierro.com)
1 points by hoaphumanoid 9y ago|0 comments
15.
Stock Price Prediction with LSTMs(miguelgfierro.com)
22 points by hoaphumanoid 9y ago|17 comments
16.
A Travellers Companion for Deep Learning Frameworks(blogs.technet.microsoft.com)
2 points by hoaphumanoid 9y ago|0 comments
17.
Introduction to Recommendation Systems with Deep Autoencoders(miguelgfierro.com)
2 points by hoaphumanoid 9y ago|0 comments
18.
A Gentle Introduction to Transfer Learning for Image Classification(miguelgfierro.com)
3 points by hoaphumanoid 9y ago|0 comments
19.
by hoaphumanoid 9y ago
Sometimes the notebook doesn't render, here there is a different option: https://nbviewer.jupyter.org/github/miguelgfierro/sciblog_su...
20.
When to Use Transfer Learning: Experimentation on Different Datasets in PyTorch(github.com)
2 points by hoaphumanoid 9y ago|1 comments
21.
Deep Learning for Entreprenerus(miguelgfierro.com)
2 points by hoaphumanoid 9y ago|0 comments
22.
by hoaphumanoid 9y ago
Miguel Fierro from Microsoft here: Joseph Sirosh session will be broadcasted live at 2.15pm ET in this link: https://myignite.microsoft.com/sessions/56555?source=session...
23.
by hoaphumanoid 9y ago
Yes, it was initially forked from an internal boosted trees library from Microsoft. The guys who created it are Microsoft Research Asia
24.
by hoaphumanoid 9y ago
The LightGBM implementation on GPU is based on this paper: https://arxiv.org/abs/1706.08359 they use several smart techniques to make the computation faster. One is how they create histograms of features that are compu
25.
by hoaphumanoid 9y ago
In deep learning, the algorithm that is used, back propagation, is basically a chained matrix multiplication, which is good for the GPU structure. However, for boosted trees the optimization problem is a little bit different, there is a sor
26.
Lessons Learned from Benchmarking Fast Machine Learning Algorithms(blogs.technet.microsoft.com)
140 points by hoaphumanoid 9y ago|20 comments
27.
Why you should use Git in software projects(miguelgfierro.com)
1 points by hoaphumanoid 9y ago|0 comments
28.
Laplace's Demon and the Scientific Method(miguelgfierro.com)
2 points by hoaphumanoid 9y ago|0 comments
29.
Fast retraining of machine learning models(github.com)
3 points by hoaphumanoid 9y ago|0 comments
30.
A notebook project on how to deploy a deep learning API(github.com)
2 points by hoaphumanoid 9y ago|0 comments

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