python


Should I Learn Machine Learning? An Intro for Beginners iD Tech

#artificialintelligence

The algorithms that form the heart of machine learning have been around for decades, but computers have only recently reached the level of processing power needed to use the techniques in practical scenarios. AI programs today can learn to identify objects in images and video, translate between languages, and even master arcade and board games. In some cases, like DeepMind's AlphaGo program, the AI even exceeds top humans at its task. Artificial intelligence (AI) refers to the field of emulating intelligence in general--anything from making a convincing opponent in a video game to an automated chatbot. Machine learning is one of the biggest fields within AI, and refers only to AI programs that are designed to learn and improve at their tasks with minimal outside input from the programmer.



Bringing Machine Learning (TensorFlow) to the enterprise with SAP HANA

@machinelearnbot

In this blog I aim to provide an introduction to TensorFlow and the SAP HANA integration, give you an understanding of the landscape and outline the process for using External Machine Learning with HANA. There's plenty of hype around Machine Learning, Deep Learning and of course Artificial Intelligence (AI), but understanding the benefits in an enterprise context can be more challenging. Being able to integrate the latest and greatest deep learning models into your enterprise via a high performance in-memory platform could provide a competitive advantage or perhaps just keep up with the competition? With HANA 2.0 SP2 onwards we have the ability to call TensorFlow (TF) models or graphs as they are known. HANA now includes a method to call External Machine Learning (EML) models via a remote source.


Hands-On Data Science and Python Machine Learning 1, Frank Kane, eBook - Amazon.com

@machinelearnbot

Very well written and easy to follow. The jupyter notebook code files available on the publisher's site make it very easy to work alongside the author as he presents the material. Arguably, one of the best introductory books on the subject if you want to dive right in with only minimal programming experience.


Leveraging Fuzzy String Matching In Competitive Intelligence

@machinelearnbot

Product comparison is one of the crucial aspects of competitive intelligence (CI). But, the greatest challenge in this journey is how to get the correct comparison product!! In this article we would explore how an NLP technique, Fuzzy String Matching (FSM), can help in accomplishing the former, especially for price tracking in e-commerce. FSM is sometimes also called as Approximate String Matching. A product is sold across multiple online channels/retailers by numerous resellers.


General Tips for Web Scraping with Python

@machinelearnbot

The great majority of the projects about machine learning or data analysis I write about here on Bigish-Data have an initial step of scraping data from websites. And since I get a bunch of contact emails asking me to give them either the data I've scraped myself, or help with getting the code to work for themselves. Because of that, I figured I should write something here about the process of web scraping! There are plenty of other things to talk about when scraping, such as specifics on how to grab the data from a particular site, which Python libraries to use and how to use them, how to write code that would scrape the data in a daily job, where exactly to look as to how to get the data from random sites, etc. But since there are tons of other specific tutorials online, I'm going to talk about overall thoughts on how to scrape.


How To Install and Use TensorFlow on Ubuntu 16.04 DigitalOcean

@machinelearnbot

TensorFlow is an open-source machine learning software built by Google to train neural networks. TensorFlow's neural networks are expressed in the form of stateful dataflow graphs. Each node in the graph represents the operations performed by neural networks on multi-dimensional arrays. These multi-dimensional arrays are commonly known as "tensors", hence the name TensorFlow. TensorFlow is a deep learning software system.


Create a Character-based Seq2Seq model using Python and Tensorflow

#artificialintelligence

In this article, I will share my findings on creating a character-based Sequence-to-Sequence model (Seq2Seq) and I will share some of the results I have found. All of this is just a tiny part of my Master Thesis and it took quite a while for me to learn how to convert the theoretical concepts into practical models. I will also share the lessons that I have learned. This blog post is about Natural Language Processing (NLP in short). It is not easy for computers to interpret texts.


Create a Character-based Seq2Seq model using Python and Tensorflow

#artificialintelligence

In this article, I will share my findings on creating a character-based Sequence-to-Sequence model (Seq2Seq) and I will share some of the results I have found. All of this is just a tiny part of my Master Thesis and it took quite a while for me to learn how to convert the theoretical concepts into practical models. I will also share the lessons that I have learned. This blog post is about Natural Language Processing (NLP in short). It is not easy for computers to interpret texts.


Stan vs PyMc3 (vs Edward) – Towards Data Science

@machinelearnbot

The holy trinity when it comes to being Bayesian. I will provide my experience in using the first two packages and my high level opinion of the third (haven't used it in practice). Of course then there is the mad men (old professors who are becoming irrelevant) who actually do their own Gibbs sampling. You specify the generative model for the data. You feed in the data as observations and then it samples from the posterior of the data for you.