IN CASE YOU MISSED IT!

BigData News Tuesday, March 13 Logistic regression, Linear regression, Watson visual recognition & more…

[vc_row][vc_column][vc_column_text]

BigData News TLDR / Table of Contents

[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”Machine-Learning-Algorithms-Which-One-to-Choose-for-Your-Problem”][vc_column width=”1/2″][vc_separator][vc_column_text]

Machine Learning Algorithms: Which One to Choose for Your Problem

[/vc_column_text][vc_column_text el_class=”topfeed-summary-list”]

  • This article will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks.
  • In this article forStatsbot, I will try to explain basic concepts and give some intuition of using different kinds of machine learning algorithms in different tasks.
  • Your goal is to find the most optimal weights w1,…wn and bias for these features according to some loss function, for example,MSEorMAEfor a regression problem.
  • More complex algorithms suffer from overfitting many features and not huge datasets, while linear regression provides decent quality.
  • Neural Networksare a new era of machine learning algorithms and can be applied for many tasks, but their training needs huge computational complexity.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: logistic regression, linear regression, algorithms, neural networks, features[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]Machine Learning Algorithms: Which One to Choose for Your Problem[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”IBM-s-Watson-plays-pokemon—AT-T-hackathon-winner”][vc_column width=”1/2″][vc_separator][vc_column_text]

IBM’s Watson plays pokemon – AT&T hackathon winner

[/vc_column_text][vc_column_text el_class=”topfeed-summary-list”]

  • I saw the Watson Visual Recognition API and wondered, what if I could get Watson to play Pokmon Go for me?
  • Using the Watson Visual Recognition API Michael created a hack that takes periodical screenshots, identifies the Pokmon characters in them, and alerts other users to where the characters are.
  • In the video below you can see the winning hacker, Michael, using our Watson IoT platform and the Watson Visual Recognition service.
  • By the end of the hackathon Stefania Kaczmarczyk, a developer evangelist for IBMs Digital Group commented Watson can track Pokmon around the world and other players can see theres a really rare one that I want really bad over here, somebody else found it, now I can go get it……
  • You can find out more aboutWatson IoT,including Watsons Visual Recognition Appalong with otherIoT APIs in the Watson Developer Cloudand read more about Michael and other hackers projects in theAT&T Shape Tech Expo site.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: Watson Visual Recognition, Watson IoT platform, Pokémon, Shape Tech Expo, AT&T Shape Tech[/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]IBM’s Watson plays pokemon – AT&T hackathon winner[/vc_column_text][/vc_column][/vc_row][vc_row el_id=”The-market-will-see-massive-regulations-DeHedge-“][vc_column width=”1/2”][vc_separator][vc_column_text]

The market will see massive regulations – DeHedge –

[/vc_column_text][vc_column_text el_class=”topfeed-summary-list”]

  • The market will see massive regulationsThere is an opinion on the market that SAFT (which is actually sale agreement for future tokens) may serve as panacea from SECs requirements to register tokens as securities or to claim respective exemption under applicable Regulation (for example, Regulation D).
  • There is also an opinion that using SAFT as part of token sale is a good strategy to escape restrictions imposed on project tokens under Regulation D.
  • That is, SAFT is considered as investment contract by itself and tokens issued under SAFT are released from such Regulation D limitations as restricted period on resale or necessity to sell only to accredited investors.
  • DeHedge suggests to be careful with such reliance on SAFT as SEC expressly explains that most tokens by themselves are investment contracts and they require separate compliance.
  • Similarly DeHedge thinks that reliance on SAFT as release from responsibility to comply with restricted period on token resale is a dangerous strategy because such solution may be easily challenged by SEC.

[/vc_column_text][vc_column_text el_class=”topfeed-tags”]Tags: SAFT, restricted period, future tokens, project tokens, [/vc_column_text][/vc_column][vc_column width=”1/2″][vc_separator][vc_column_text el_class=”topfeed-tweet”]

[/vc_column_text][vc_column_text el_class=”topfeed-embedly”]The market will see massive regulations – DeHedge – Medium[/vc_column_text][/vc_column][/vc_row]

Top Big Data Courses

The Ultimate Hands-On Hadoop - Tame your Big Data! (31,889 students enrolled)

By Sundog Education by Frank Kane
  • Design distributed systems that manage "big data" using Hadoop and related technologies.
  • Use HDFS and MapReduce for storing and analyzing data at scale.
  • Use Pig and Spark to create scripts to process data on a Hadoop cluster in more complex ways.
  • Analyze relational data using Hive and MySQL
  • Analyze non-relational data using HBase, Cassandra, and MongoDB
  • Query data interactively with Drill, Phoenix, and Presto
  • Choose an appropriate data storage technology for your application
  • Understand how Hadoop clusters are managed by YARN, Tez, Mesos, Zookeeper, Zeppelin, Hue, and Oozie.
  • Publish data to your Hadoop cluster using Kafka, Sqoop, and Flume
  • Consume streaming data using Spark Streaming, Flink, and Storm

Learn more.


Taming Big Data with MapReduce and Hadoop - Hands On! (13,894 students enrolled)

By Sundog Education by Frank Kane
  • Understand how MapReduce can be used to analyze big data sets
  • Write your own MapReduce jobs using Python and MRJob
  • Run MapReduce jobs on Hadoop clusters using Amazon Elastic MapReduce
  • Chain MapReduce jobs together to analyze more complex problems
  • Analyze social network data using MapReduce
  • Analyze movie ratings data using MapReduce and produce movie recommendations with it.
  • Understand other Hadoop-based technologies, including Hive, Pig, and Spark
  • Understand what Hadoop is for, and how it works

Learn more.