Tech Index




NLP: natural language processing
  1. The Art of Tokenization
  2. Part-of-Speech Lookup Tables and Frequency Distributions
  3. Jaccard Similarity
  4. Phonetic Algorithms
  5. TF/IDF with Google n-Grams and part-of-speech Tags
  6. Well, well, well ... Word Sense Disambiguation (WSD) with Google n-Grams
  7. A Visual Introduction to Phrase Structure and Dependency Parsing
  8. Same but not the Same: Homonym Frequency Distributions
  9. Auto-Generation of Regular Expressions for Spelling Errors
  10. Snowball Stemmer for Java
  11. SKOS Recipe for Stemming
  12. Language Modeling
  13. Natural Language Understanding of Unstructured Data
  14. Precision vs Recall in Dictionary Matching
  15. [PPT] Natural Language Classification on Bluemix
  16. Triple Extraction
    1. Straight-up Triples (1-6)
    2. Intransitive Action (2-6)
    3. Modeling Business Scenarios (3-6)
    4. Modeling Perception (4-6)
    5. Modeling Characteristics (5-6)
    6. Spatial Modeling (6-6)
    7. Extracting IS-A Relationships
  17. Alchemy API:
    1. Using the Taxonomy Tagger and Source Code


Provenance: a digital record
  1. W3C Provenance Standard (I was a member of the working group)
  2. W3C Provenance Model Primer
  3. PROV and Dublin Core
  4. Provenance and Compliance Risk Management
  5. Reification and Trust
    1. [PPT] Things and Strings
  6. [PPT] PROV-O Overview


Machine Learning: learning from data
  1. The Road to Gamma
  2. The Chain Rule of Probability
  3. Octave: A Simple Prototyping tool for Machine Learning


Graphs: entities and relationships
  1. [PPT] Ontologies and Semantic Web
  2. Inference using OWL 2.0 Semantics
  3. Semantic Relationships in Wordnet
  4. Distinguishing Parts from Kinds
  5. BGS Open Data Review:
    1. Geochronology Ontologies
    2. Earth Material Ontologies
  6. NLP-Driven Ontology modeling for Ontology-driven NLP
  7. Ontology-driven Natural Language Processing
  8. An Omonastic Compilation and Ontology
  9. Model Simplification through Dependency Reinjection
  10. Neo4j
    1. Neo4j and Python on Ubuntu (using VirtualBox)





Jena: a java system for rdf
  1. Jena: A Semantic Web Framework (Introduction)
  2. The Jena Schemagen Tool
  3. The Jena Layer Cake



Apache Hadoop: reliable, scalable cluster computing
  1. Software Installation
    1. Windows:
      1. Virtualbox for Virtualization
      2. Installing PuTTY
    2. Linux:
      1. Installing Java
      2. for Development Environments only:
        1. Installing Maven
        2. Installing Eclipse
        3. Develop your Environment
  2. Creating the Cluster
    1. Bring the Binaries
    2. Secure the Channel
    3. Configure the Base
    4. Cloning for Clusters
      1. Adding a new DataNode
  3. Using the Cluster
    1. Flip the Switch
    2. Copy some Files
    3. Submit a Job
    4. Monitor your Progress
  4. Understanding the Hadoop Architecture
  5. Troubleshooting
    1. Incompatible Cluster IDs
    2. GC Overhead Limit Exceeded



Apache Spark: lightning fast cluster computing
  1. Installing Spark on Ubuntu
  2. Spark RDD (Resilient Distributed Dataset) Introduction and API
  3. Deploy a Scala Job to a Spark Cluster using SBT
  4. PySpark Recipes



Scala Lang: OO and java interoptable lang
  1. Installing Scala on Ubuntu
  2. Installing sbt on Ubuntu



Python: the Python Programming Language
  1. Installation and Configuration:
    1. Configuring a Python Development Environment on Ubuntu
    2. Exposing a Python App via Django in Vagrant
  2. MongoDB
    1. Installing the Python Driver in MongoDB
    2. Importing Data into MongoDB using Python
  3. Requests Module
    1. GET and POST with Requests
    2. Posting documents to Solr 
  4. Zeppelin and Pyspark
    1. Writing to Parquet
    2. Transform a CSV to Parquet
    3. Merge Multiples CSVs in one Dataframe
    4. Finding Associated Hashtags (Contexual Analysis)
    5. Ad-hoc Social Analysis in Twitter  
    6. Pyspark Operations Overview
    7. Pyspark Recipes 
  5. Other
    1. Using the Slack RTM API
    2. Pandas and Geonames 
    3. Using Paramiko for SSH-based operations 
    4. Using Selenium to logon to Twitter 
    5. Bulk Inserts to MySQL 



Java: general-purpose computer programming language
  1. Installing the JDK on Ubuntu
  2. Servlets
    1. Servlet Redirecting and Dispatching
    2. Servlet Mapping
  3. Spring
    1. The Spring Container for IoC (Inversion of Control) 
    2. Loading Resources from the Local File System
    3. Data Access
      1. Using the JDBC  Template
      2. Spring JPA
  4. Jersey
    1. An Introduction to Java API for RESTful Web Services (JAX-RS)
    2. Deploying a RESTful Web Service onto Tomcat (running in a Docker Container)
    3. JAX-RS and MongoDB (using Docker)
  5. Public Contributions on Github:
    1. java-commons, jaxrs-minimalist, jaxrs-mongo, snowball (maven-compatible)



Docker: an open platform for distributed apps
  1. Installing Docker
    1. on Ubuntu
    2. on Mac OS
  2. Docker Design and Architecture
  3. Creating your own Dockerfile
  4. Docker and ...
    1. Apache Tomcat
    2. Apache Solr
  5. Public Contributions on Github



MySQL: a popular open-source database
  1. MySQL Installation on Ubuntu
  2. Using the MySQL Workbench
  3. Essential Admin Tasks



Maven: a build automation tool
  1. Installing Maven
  2. Creating a Java Project with Maven
  3. Using Profiles in Maven
  4. Project Object Model (POM) Overview
  5. Multi-Workspace Structuring Best Practices
  6. Installing a Local JAR
  7. Creating an Executable JAR
  8. Deploying a Web Project (without Eclipse)
  9. Dependency Visualization
  10. Parent POMs and the Maven Reactor
  11. Public Contributions on Github (BOMs)



Tomcat: an open-source web server and servlet container
  1. Deploying to Tomcat without an IDE using Maven
  2. Docker and Apache Tomcat


MongoDB: an open-source document database
  1. Installation
    1. Installation on Ubuntu
    2. MongoDB and Docker
  2. Changing the Data Path (dbPath)
  3. Installing the RoboMongo Administrative Client
  4. An Introduction to the Aggregation Pipeline
  5. Java
    1. Using the Java Driver
    2. Using Spring Data for MongoDB
    3. JAX-RS and MongoDB
  6. Python
    1. Installing the Python Driver
    2. Importing Data using PyMongo


Lucene: a high-performance search engine library
  1. Building the Search Index
  2. Querying the Search Index
  3. Query Expansion with Wordnet Synonyms

Solr: an enterprise search platform (built on Lucene)
  1. Introduction to Solr (on Docker)
  2. Posting documents to Solr
  3. Automated Tokenization testing with Solr

Bluemix: an open-standards cloud platform
  1. Configuring a Local Development Environment
  2. Docker-in-docker Dockerfile for Deploying Docker to Bluemix
  3. [PPT] Creating a Git Project (on Bluemix)
  4. [PPT] Building a Project with Maven (on Bluemix)
  5. [PPT] Deploying a Java Web App (on Bluemix)
  6. [PPT] Training the NL Classifier on Bluemix


Github: revision control and scm
  1. Installation on Ubuntu
  2. Clone a Remote Repository


Ubuntu: debian linux distribution
  1. Mounting a Network Share


Jenkins: continuous integration
  1. Installing Jenkins (with Git and Maven) on Ubuntu 14.04
  2. Using Jenkins (with Git and Maven)
  3. [PPT] Jenkins on Docker


Eclipse: ide for java developers
  1. Installing Eclipse on Ubuntu


VirtualBox: enterprise virtualization
  1. Cloning VirtualBox VMs
  2. Adding a new Hard Drive to Ubuntu 14.04


NodeJS: javascript on the server
  1. Installing node.js on Ubuntu 14.10
  2. Installing express.js on Ubuntu 14.10
  3. Node and Express on OS X


SAS: Analytics Software & Solutions
  1. Reading a CSV
  2. PROC Means
  3. PROC Freq
  4. PROC Print

10 comments:

  1. soumyaJune 20, 2018 at 2:52 AM

    I read this blog it has good information to learn more and more once check it here Devops Online Training Hyderabad To get more knowledge on Devops.

    ReplyDelete
  2. UnknownSeptember 6, 2018 at 2:29 AM

    Thanks for giving a great information about DevOps Good Explination nice Article
    anyone want to learn advance devops tools or devops online training
    DevOps Online Training
    DevOps Online Training hyderabad
    DevOps Training
    DevOps Training institute in Ameerpet

    ReplyDelete
  3. mist hyderabadJanuary 1, 2019 at 3:50 AM

    Thank u for this information
    http://www.mistltd.com

    ReplyDelete
  4. zaraJanuary 2, 2019 at 1:07 AM

    Best theoretical explanation for Devops Training in Hyderabad.

    ReplyDelete
  5. mytrainingsolineFebruary 7, 2019 at 10:34 PM


    Nice blog..! I really loved reading through this article... Thanks for sharing such an amazing post with us and keep blogging...
    Devops online training
    Best Devops online training
    Devops online training in Hyderabad
    Devops online training in india

    ReplyDelete
  6. Azure DevOpsMarch 6, 2020 at 11:13 PM

    Very useful information, the post shared was very nice.
    DevOps Online Training

    ReplyDelete
  7. UnknownJanuary 31, 2022 at 4:18 AM

    tiktok jeton hilesi
    tiktok jeton hilesi
    binance referans kimliği
    gate güvenilir mi
    tiktok jeton hilesi
    paribu
    btcturk
    bitcoin nasıl alınır

    ReplyDelete
  8. BeratMarch 27, 2022 at 8:46 AM

    bitcoin nasıl alınır
    bitcoin nasıl alınır
    bitcoin nasıl alınır
    bitcoin nasıl alınır
    binance referans kimliği nedir
    gate io güvenilir mi
    btcturk batar mı
    takipçi satın al

    ReplyDelete
  9. python.dataSeptember 24, 2026 at 12:52 AM

    GREAT

    ReplyDelete
  10. python.dataSeptember 24, 2026 at 12:53 AM

    **NLP (Natural Language Processing)** is a branch of **Artificial Intelligence (AI)** that helps computers understand, process, and analyze human language. In **Data Analytics**, NLP can be used to extract useful information from text data such as customer reviews, emails, social media comments, and survey responses.PySpark Course. Common tasks include **sentiment analysis, text classification, keyword extraction, language translation, and text summarization**. Python libraries such as **NLTK, spaCy, and Transformers** are commonly used for NLP applications. By analyzing large volumes of text, NLP helps organizations identify **customer opinions, trends, patterns, and insights** that can support better decision-making.

    ReplyDelete

Subscribe to: Posts (Atom)