Machine learning and statistics with python

Select Language Afrikaans Albanian Arabic Armenian Azerbaijani Basque Belarusian Bulgarian Catalan Chinese (Simplified) Chinese (Traditional) Croatian Czech Danish Dutch English Estonian Filipino Finnish French Galician Georgian German Greek Haitian Creole Hebrew Hindi Hungarian Icelandic Indonesian Irish Italian Japanese Korean Latvian Lithuanian Macedonian Malay Maltese Norwegian Persian Polish Portuguese Romanian Russian Serbian Slovak Slovenian Spanish Swahili Swedish Thai Turkish Ukrainian Urdu Vietnamese Welsh Yiddish Bengali Gujarati Marathi Nepali Punjabi Tamil Telugu Introduction:  In our previous post , we discussed about the basic nlp works using spacy. If you have not read that post, read that post now for better understanding. Today we are going to discuss dependency parsing using spaCy. This is the second post of our spacy exploration series. What is dependency parsing? dependency parsing is the analyzing of a sentence in grammatical way, to establish the gram

On a very bright sunny day, I decided to download the psychopy software to create some  psychology tests on python. But as soon as I did that, I couldn't open the same. I will discuss in this very small post, how I solved that issue. First, I downloaded 2020.1.3. version  using the tar file download process explained in the official site. But that didn't work out. Neither the app would open nor it would show any error message in the terminal. Then my instructor said that he is using 2020.2.4 version in mac. Having that information, I first uninstalled the 1.3. version and then wrote  pip3 install psychopy==2020.2.4 Now, I got a error in my terminal saying something like: ImportError: libwebkitgtk-3.0.so.0: cannot open shared object file: No such file or directory Now on searching this in google, you will see that this is a psychopy github issue . Which basically tells you to install the libwebkitgtk of the said version. So you have to type: sudo apt-get install libwebkitg

 Introduction:  spaCy is an open source natural language software library for advanced natural language processing, written in 2015 by explosion ai founders Matthew Honnibal and Ines Montani. While NLTK is mainly used for teaching nlp concepts and research, spaCy is one of the most famous packages used in production for companies world-wide. Before spaCy, the market was lacking of a production level great packages, which people would integrate to their services and use the best nlp services present. And spaCy exactly did that. To quote Mr.Honnibal from '15,   " spaCy is a new library for text processing in Python and Cython. I wrote it because I think small companies are terrible at natural language processing (NLP). Or rather: small companies are using terrible NLP technology. " spaCy is a industrial library which is written on python and cython; and provides support for TensorFlow, PyTorch, MXNet and other deep learning platforms. In this post, we will explore the dif

  Now Data science is the vital asset of any organization. It's hard to imagine life without data. And companies are realizing the importance of it. In basic terms, Data science extracts meaningful insights from many structural and unstructured data. Data science is the field of research where we learn about programming skills, domain expertise, and knowledge of mathematics & statistics. Furthermore, data science uses machine learning algorithms in various formate like numbers, text, images, audio, video, and more which helps to perform tasks without human effort by artificial intelligence (AI) system. so it's hard to describe a specific definition because when we applied to different fields it begins with incredible new insights. After the lockdown effect Data science is the most growing and demanding field. and as by Glassdoor research data scientist is ranked at the third-best job in America for 2020. And according to LinkedIn listed data scientist

Lot of us start our career as a data analyst and use a lot of excel before using programming language to write custom codes. As my career has grown, I didn't cross excel as my primary working tool ever yet. That has proven bad in some cases and has made me a python freak in its own way.  Now, I had to present something using excel and perform all the calculations in excel. But I had all the tasks done using simple python dict, list and math functions. Now, I had to translate all these python things into small small excel calculations. Here comes the motivation for this post; to point out simple tasks from python into excel. Caution: all though this will be a small collage of tasks at first, I will keep adding more tasks later on. First task: (1) I have two lists. One contain ratings of restaurants, while the other one contains their gross rating i.e. good, bad and average; encoded in 0,1,2. In python, I used a dictionary with keys 0,1,2 and looped through the list of rating to

Select Language Afrikaans Albanian Arabic Armenian Azerbaijani Basque Belarusian Bulgarian Catalan Chinese (Simplified) Chinese (Traditional) Croatian Czech Danish Dutch English Estonian Filipino Finnish French Galician Georgian German Greek Haitian Creole Hebrew Hindi Hungarian Icelandic Indonesian Irish Italian Japanese Korean Latvian Lithuanian Macedonian Malay Maltese Norwegian Persian Polish Portuguese Romanian Russian Serbian Slovak Slovenian Spanish Swahili Swedish Thai Turkish Ukrainian Urdu Vietnamese Welsh Yiddish Bengali Gujarati Marathi Nepali Punjabi Tamil Telugu   A * algorithm is a searching algorithm that searches for the shortest path between the   initial and the final state. It is used in various applications, such as maps . Searching Algorithm follows two technique such as Bfs(Breadth First Search) Dfs(Depth First Search) Breadth First Search is a vertex based technique for finding the shortest path in a graph. It  uses a Queue data structure which