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All Blog Posts Tagged 'Python' (14)

Python for Automating Your Quality Analysis

Analyzing the quality of your software is crucial to any business. The process appears towards the end of your software development lifecycle but indeed decides the fate of it. In other words, quality analysis demonstrates a process in which the actual output of the software is tested with its expected output. There are a variety of test inputs that are used in the process of quality analysis so that the product sheds light on the actual truth of where it…

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Added by Divyesh Aegis on November 7, 2019 at 11:00pm — No Comments

Python as a tool benefiting data scientists in many ways

Being extremely versatile general purpose, professional programming language, Python offers plenty of applications. Python language is user-friendly and simple to grasp and this made it popular throughout the world. Python plays a critical role for data scientists to find out lucrative job opportunities. 

Today, Python has become the most in-demand programming language in the data science world. Python offers an extensive range…

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Added by Divyesh Aegis on September 5, 2019 at 12:00am — No Comments

Why is Python a Top Choice of the data analytics?

Python is an extremely popular programming language. It is not just apt for generic purposes but it is extremely easy to read and use as well. The main reason why Python is used by a majority of people these days is the fact that it allows the programmers to save their time by using only limited lines of codes. In order to accomplish tasks, the developers do not have to spend a lot of time on coding, unlike the other languages. Rather, all they can do is, spend time on…

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Added by Divyesh Aegis on July 25, 2019 at 12:53am — No Comments

Machine Learning with Signal Processing Techniques

Stochastic Signal Analysis is a field of science concerned with the processing, modification and analysis of (stochastic) signals.

Anyone with a background in Physics or Engineering knows to some degree about signal analysis techniques, what these technique are and how they can be used to analyze, model and classify signals.

Data Scientists coming from a different fields, like Computer Science or Statistics, might not be aware of the analytical power these techniques bring with…

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Added by ahmet taspinar on April 29, 2018 at 9:00am — No Comments

The Perceptron Algorithm explained with Python code

1. Introduction

Most tasks in Machine Learning can be reduced to classification tasks. For example, we have a medical dataset and we want to classify who has diabetes (positive class) and who doesn’t (negative class). We have a dataset from the financial world and want to know which customers will default on their credit (positive class) and which customers will not (negative class).

To do this, we can train a Classifier with a ‘training dataset’ and after such a Classifier is…

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Added by ahmet taspinar on December 22, 2016 at 10:30am — No Comments

Deep Learning in Python: Getting Started

Deep learning is all the rage. You hear about it in the news, you read it about it in the news and it’s all over popular culture as well. What’s more, it’s revolutionizing the tech industry, as computers teach…

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Added by Malia Keirsey on December 5, 2016 at 12:00pm — No Comments

Machine Learning with Python- Why do they form the best combination

Machine Learning is being hailed as “Next Generation Analytics”.Machine Learning tasks can be roughly classified as –

  • Getting the data
  • Cleaning the data…
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Added by Ivy Pro School on April 11, 2016 at 5:57am — No Comments

Calculation cases of Link Relative Ratio and Year-on-year Comparison in data analytics

Cross-row and group computation often involves computing link relative ratio and year-on-year comparison. Link relative ratio refers to comparison between the current data and data of the previous period. Generally, it takes month as the time interval. For example, compare the sales amount of April with that of March, and the growth rate we get is the link relative ratio of April. Hour, day, week and quarter can also be used as the time…

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Added by Jessica May on September 22, 2014 at 2:00am — No Comments

A Method of Grouping and Summarizing Data of Big Text Files in R Language

It is common to use R language to group and summarize data of files. Sometimes we may find ourselves processing comparatively big files which have smaller computed result and bigger source data. We cannot load them wholly to the memory when we need to compute them. The only solutions could be batch importing and computing as well as result merging. We’ll use an example in the following to illustrate the way of R language to group and summarize data from big text files.

Here is a file,…

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Added by Jessica May on August 24, 2014 at 8:54pm — 2 Comments

(R + Python)

Both R & Python should be measured based on their effectiveness in advanced analytics & data science. Initially, as a new comer in data science field we spend good amount of time to understand the pros and cons of these two. I too carried out this study solely for “self” to decide which tool should i pick to get in depth of data science. Eventually, i have started realizing that both (R & Python) has its space of mastery along with their broad support to data science. Here some…

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Added by Manish Bhoge on February 7, 2014 at 11:22pm — No Comments

Python Scikit-learn to simplify Machine learning : { Bag of words } To [ TF-IDF ]

Text (word) analysis and tokenized text modeling always give a chill air around ears, specially when you are new to machine learning. Thanks to Python and its extended libraries for its warm support around text analytics and machine learning. Scikit-learn is a savior and excellent support in text processing when you also understand some of the concept like "Bag of word", "Clustering" and "vectorization". Vectorization is  must-to-know technique for all machine leaning learners, text miner…

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Added by Manish Bhoge on September 25, 2013 at 12:30pm — No Comments

An indispensable Python : Data sourcing to Data science.

Data analysis echo system has grown all the way from SQL's to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run…

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Added by Manish Bhoge on August 27, 2013 at 11:00am — 1 Comment

SQL CREATE TABLE in Pandas (Python) -- should be straightforward, but...

My new blog post on how to do the equivalent of SQL's "CREATE TABLE" in the Pandas Python Data Analysis Library. Sounds simple, but I wasn't able to find such an example anywhere on the web.
http://technicaltidbit.blogspot.com/2013/06/create-empty-dataframe-in-pandas.html

Added by Michael Malak on June 26, 2013 at 1:29pm — No Comments

Query Hive from iPython Notebook

My new blog post on querying Hive from iPython Notebook with pandas, the Python alternative to R:

 

http://technicaltidbit.blogspot.com/2013/06/query-hive-from-ipython-notebook.html

Added by Michael Malak on June 13, 2013 at 9:44am — No Comments

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