kmax12

10 ms·

61.
by kmax12 7y ago
This reminds me of a story I heard from Charlie Munger of Berkshire Hathaway about asking Mozart for advice. One man came to Mozart and asked him how to write a symphony. Mozart replied, “You are too young to write a symphony.” The man said
62.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
63.
by kmax12 7y ago
I agree. My experience has been that most machine learning tools help answer a question, but don't provide APIs and method to help you define the specific question you want to solve. This is actually why I work on an open source librar
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WeWork Parent to Name Real-Estate Veteran Sandeep Mathrani New CEO(wsj.com)
1 points by kmax12 7y ago|0 comments
65.
by kmax12 7y ago
I know I'm not the only one, but it's hard to imagine doing my job the last several year without Pandas. Even though Pandas has been used in production by many people as basically a 1.0.0 release for a long time, this an amazing m
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by kmax12 7y ago
Part of the problem is that if you gave 20 developers/data scientists/ml engineers the same the set of data and asked them the do data prep and feature engineering, you'd probably have them come back with 20 different approac
67.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
68.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
69.
Automatic Dataset Normalization in Python(blog.featurelabs.com)
3 points by kmax12 7y ago|0 comments
70.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
71.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
72.
by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
73.
Debugging Your Startup(atrium.co)
176 points by kmax12 7y ago|14 comments
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The BS-Industrial Complex of Phony A.I(gen.medium.com)
1 points by kmax12 7y ago|0 comments
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by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com At Feature Labs, we’re building automation technology to make machine learning easier to use. We work on many unique and imp
76.
Debugging Your Startup(atrium.co)
3 points by kmax12 7y ago|0 comments
77.
by kmax12 7y ago
I think it’s a bit of an overstatement to call this an end-to-end solution. What they are starting with here is a single table of data with all the features already defined and an existing binary label column. Typically when this type of da
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(In)convenient Truths About Applied Machine Learning(slideshare.net)
2 points by kmax12 7y ago|0 comments
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by kmax12 7y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site | https://www.featurelabs.com Even though some companies have already found success with machine learning, the vast majority of organizations large and sm
80.
by kmax12 7y ago
I see this as a very timely question. As ML has proliferated, so has the number of ways to construct machine learning pipelines. This means that from one project to another the tools/libraries change, the codebases start looking very d
81.
by kmax12 7y ago
This is very important! If you use Featuretools, we provide a mechanism to avoid this very problem. See how we handle time in our documentation here: https://docs.featuretools.com/automated_feature_engineering/...
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by kmax12 8y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site or Remote | https://www.featurelabs.com Feature Labs develops automation technology to make it easier for companies to create machine learning application
83.
by kmax12 8y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site or Remote | https://www.featurelabs.com Feature Labs makes it easier for companies to build machine learning applications. We build a web app and develope
84.
by kmax12 8y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site or Remote | https://www.featurelabs.com Feature Labs makes it easier for companies to build machine learning applications. We build a web app and develope
85.
Predicting the real-time availability of 200M grocery items(tech.instacart.com)
2 points by kmax12 8y ago|0 comments
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by kmax12 8y ago
To get started, I'd pick the most important business problem you have and then solve it using the simplest machine learning approach. You mentioned using Pytorch. Instead, I recommend a classical machine learning using a library like s
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by kmax12 8y ago
I definitely see the need for packages like this. So much of a data scientist's time is spent on feature engineering, but there are relatively few tools out there that are trying to improve that step in the process compared to tools fo
88.
by kmax12 8y ago
Feature Labs, Inc. | Software Engineer | Boston, MA | Full-time | On-site or Remote | http://www.featurelabs.com Feature Labs is changing the way companies create new machine learning products and services. We make a web app and
89.
How to Create Value with Machine Learning(towardsdatascience.com)
2 points by kmax12 8y ago|0 comments
90.
by kmax12 8y ago
cool! any plans to come to other cities?

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