Showing posts with the label models

HBASE Vs. RDBMS Top Differences You can Unlock Now

HBASE in the Big data context has a lot of benefits over RDBMS. The listed differences below make you understandable why HBASE is popular in Hadoop (or Bigdata) platform. Let us check one by one quickly. HBASE Vs. RDBMS Differences Random Accessing HBase handles a large amount of data that is store in a distributed manner in the column-oriented format while RDBMS is systematic storage of a database that cannot support a random manner for accessing the database. Database Rules RDBMS strictly follow Codd's 12 rules with fixed schemas and row-oriented manner of database and also follow ACID properties. HBase follows BASE properties and implement complex queries. Secondary indexes, complex inner and outer joins, count, sum, sort, group, and data of page and table can easily be accessible by RDBMS. Storage From small to medium storage application there is the use of RDBMS that provide the solution with MySQL and PostgreSQL whose size increase with concurrency and performance.  Codd'

2 Top Python Libraries to Create ML model

To Create a Model of Machine Learning in Python, you need TWO libraries. One is 'NUMPY' and the other one is 'PANDAS'. 2 Top Libraries You Need To Build a model of Machine learning you need the right kind of data. So, use the data for your project should be refined. Else, it will not produce correct results. The prime steps are Data Analysis and Data Preprocessing. NUMPY - It has the capabilities of Calculations. PANDAS- It has the capabilities of Data processing. How Install Python Machine Learning Libraries  import  NumPy as np # linear algebra import pandas as PD # data processing, CSV file I/O (e.g. PD.read_csv) How to Check NumPy/Pandas installed After '.' you need to give double underscore on both sides of the version.  How Many Types of Data You Need You need two types of data. One is data to build a model and the other one is data you need to test the model. Raw data Evaluate-data How to Build a Model Flowchart I have given a f

Real thoughts on IBM power8 servers to use on analytics

IBM Servers International Business Machines Corp, in its latest attempt at reviving demand for its hardware products, is launching high-end system servers that it says are 50 times faster than its closest competitor at analysing data.  The POWER8 servers , the product of a $2.4 billion, three-year investment, are part of the company's decade-long shift to higher-value hardware technology.    IBM  said the machines are 50 times faster than the low-end x86-based servers it sold to Chinese PC maker  Lenovo  Group Ltd in January.  The technology services provider said on Wednesday it hopes the servers, designed for large-scale computing, will appeal to clients looking to manage new types of social and mobile computing and mass amounts of data. Last week, the company reported its lowest quarterly revenue in five years, weighed down by falling demand for its storage and server products. IBM dominates the higher-end server market with 57 percent market share, according to res