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Embitsol Embedded Software / Automotive / IoT , India
$15 /hr
10 Years Exp.
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Verticals: Embedded software development IT Services QA / testing service Domains Embedded product development Automotive IoT AUTOSAR languag...Read More
Arvind S.Senior Consultant , India
$8 /hr
8 Years Exp.
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I’m network security engineer with 8 plus experience in enterprise and ISP networking. I have worked on all major firewalls like Cisco asa, checkpoin...Read More
Darshan N.Network engineer and Python developer, India
$100 /hr
4 Years Exp.
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I am responsible for Architecting & Developing Network Management solutions for Data Center Switches. Cloud based Network Design Tools,Configuring...Read More
Adarsh B.Senior IoT Design Engineer , India
$100 /hr
4 Years Exp.
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Linkedin: https://www.linkedin.com/in/adarsh-b-u-70640792/ Experience on ZiGbee, Bluetooth, Z-Wave, 6LoWPan and WLAN I'm an IoT based enthu...Read More
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Python is one of the fastest growing programming languages. It has undergone more than 28 years of the successful span. Python itself reveals its success story and a promising future ahead. Python programming language is presently being used by a number of high traffic websites including Google, Yahoo Groups, Yahoo Maps, Shopzilla, Web Therapy, Facebook, NASA, Nokia, IBM, SGI Inc, Quora, Dropbox, Instagram and Youtube. Similarly, Python also discovers a countless use for creating gaming, financial, scientific and instructive applications.

 

Python is a fast, flexible, and powerful programing language that's freely available and used in many application domains. Python is known for its clear syntax, concise code, fast process, and cross-platform compatibility.

 

Python is considered to be in the first place in the list of all AI and machine learning development languages due to the simplicity. The syntaxes belonging to python are terribly easy and can be easily learn. Therefore, several AI algorithms will be easily implemented in it. Python takes short development time as compared to different languages like Java, C++ or Ruby. Python supports object oriented, functional as well as procedure oriented styles of programming. There are lots of libraries in python that make our tasks easier.

 

Some technologies relying on python:

Python has become the core language as far as the success of following technologies is concerned. Let’s dive into the technologies which use python as a core element for research, production and further developments.

 

  1. Networking: Networking is another field in which python has a brighter scope in the future. Python programming language is used to read, write and configure routers and switches and perform other networking automation tasks in a cost-effective and secure manner.
  2. Big Data: The future scope of python programming language can also be predicted by the way it has helped big data technology to grow. Python has been successfully contributing in analyzing a large number of data sets across computer clusters through its high-performance toolkits and libraries.
  3. Artificial Intelligence (AI): There are plenty of python frameworks, libraries, and tools that are specifically developed to direct Artificial Intelligence to reduce human efforts with increased accuracy and efficiency for various development purposes. It is only the Artificial Intelligence that has made it possible to develop speech recognition system, interpreting data like images, videos etc.

 

Why Choose Python for Artificial Intelligence and Machine Learning?

Whether a startup or associate MNC, Python provides a large list of benefits to all. The usage of Python is specified it cannot be restricted to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complicated processes like artificial intelligence (AI), Machine Learning (ML), natural language process, data science etc. The question is why Python is gaining such momentum in AI? And therefore the answer lies below:

 

Flexibility: Flexibility is one of the core advantages of Python. With the option to choose between OOPs approach and scripting, Python is suitable for every purpose. It works as a perfect backend and it also suitable for linking different data structures together.

 

Platform agnostic: Python provides developer with the flexibility to provide an API from the existing programming language. Python is also platform independent, with just minor changes in the source codes, you can get your project or application up and running on different operating systems.

 

Support: Python is a completely open source with a great community. There is a host of resources available which can get any developer up to speed in no time. Not to forget, there is a huge community of active coders willing to help programmers in every stage of developing cycle.

 

Prebuilt Libraries: Python has a lot of libraries for every need of your AI project. Few names include Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning.

 

Less Code: Python provides ease of testing - one of the best among competitors. Python helps in easy writing and execution of codes. Python can implement the same logic with as much as 1/5th code as compared to other OOPs languages.

 

Applications of Python:

There are so many applications of Python in the real world. But over time we’ve seen that there are three main applications for Python

Web Development: Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

Data Science (including Machine Learning): Machine Learning with Python has made it possible to recognize images, videos, speech recognition and much more.

Data Analysis/Visualization: Python is also better for data manipulation and repeated tasks. Python helps in the analysis of a large amount of data through its high-performance libraries and tools. One of the most popular Python libraries for the data visualization is Matplotlib.

 

A large number of people think that “freelancing” is something you do when you cannot get a real job. On the other hand, “freelancers” know that there is nothing more real than that to be the owner, director, and the financial manager at the same time.

 

Freelancing is basically being self-employed and not committed to any one company or firm. You’ve heard those seemingly perfect freelance stories. Some designer quits his jobs and starts freelancing and now he’s making more money than he was while at a firm. All the while travelling the world and working for himself. Not to mention he gets to choose what kind of work he does.

 

When I say “full-time job” I mean one that’s 30-hours per week or more. Basically, you’ve hit the threshold for wherever you’ve started to receive benefits for the time you work each week. Generally, over 30-hours is considered regular, and 40-hours is that the “traditional” hours for full time, however many jobs will go over that mark.

 

When you work as a freelancer, you’re not permanently employed by any one company. You may have a long-term contract, however freelancers are usually working with totally different employers at any given time and should have a spread of tasks that they'll be employed for.

 

“I choose to be in freelance because I’m able to work my own hours, determine my own salary, and be creative in my work.”

Freelance work offers tremendous advantages and can represent an attractive alternative to a traditional job. If you are considering a freelance career, you should explore the benefits of freelancing. 

  1. Working from home: Working from home is a perfect resolution for balancing work and family or personal life, during which you can with success make for a living and support yourself and your family. Engaging from home and thereby carve out a comfortable life, it's fully possible. But, as long as you're willing to work hard.
  2. Flexibility of hours: Working from home or from a remote workplace as a freelancer allows you to dictate your own hours and work on times most convenient to you. Freelancers with young kids, for instance, will work when the children are sleeping; freelancers with traditional employment or part-time jobs will perform their freelance work around their regular work hours.
  3. Perform multiple task as same time: Large Scale Company engaged in one activity or an entrepreneur who knows how to do five things at once? Freelancers are themselves in their work. That speaks to that they constantly further educate, constantly wide network of contacts and work hard at acquiring new skills that can make them more competitive in the work they are dealing with.
  4. Lower Cost: Utility costs, equipment, insurance, and running the business from the office building has become too costly. If the profit is insufficient, jobs will fail because of the buildup of these costs. Freelancers, on the other hand, almost don't have any additional cost, then will get started by simply registering at premium freelancing sites like Toogit.
  5. Freedom: As a freelancer, you can choose the clients you wish to work with and the projects on which you work, particularly if you have an excess of work. You can drop high maintenance or slow-paying clients or turn down undesirable projects if you desire.
  6. Income Control: Your income is the direct results of your own efforts instead of being set by the law firm or company. In most cases, the harder you work, the greater the reward. Your paycheck or bonus will not be capped, reduced or eliminated by your leader, though it will vary month to month, depending on your efforts and business.
  7. Learning through Work: Do not think about work like at a company wherever you work twenty years the same thing, you'll change jobs and employers on a weekly basis, and lots of additional can learn what is going to be helpful for future jobs.
  8. Full credit: When you work as a freelancer, you receive full credit for your work. You don't have to worry about the blunders of other employees, compromising your work product for the sake of the team or others taking credit for your work.
  9. Opportunity for all: Increasing employment of vulnerable teams like mothers and fathers with young kids, people with mobility problems and people living in remote areas.

 

“I prefer the freedom to choose what sort of work I do without my schedule being controlled and my choices being commanded by someone else. I can express myself and be appreciated for it as well as bring beauty to the world by way of my work. It also is less stressful than an office environment and allows me the time necessary to take care of my farm.”

A chatbot is an artificial intelligence powered piece of software in a device, application, web site or alternative networks that try to complete consumer’s needs and then assist them to perform a selected task. Now a days almost every company has a chatbot deployed to interact with the users.

 

Chatbots are often used in many departments, businesses and every environment. They are artificial narrow intelligence (ANI). Chatbots only do a restricted quantity of task i.e. as per their design. However, these Chatbots make our lives easier and convenient. The trend of Chatbots is growing rapidly between businesses and entrepreneurs, and are willing to bring chatbots to their sites. You might also produce it yourself using Python.

 

How do chatbots work?

There are broadly two variants of chatbotsRule-Based and Self learning.

  1. In a Rule-based approach, a bot answers questions based on some rules on that it is trained on. The rules outlined could be very easy to very complicated. The bots will handle easy queries but fail to manage complicated ones.
  2. The Self learning bots are those that use some Machine Learning-based approaches and are positively a lot of economical than rule-based bots. These bots may be of additional two types: Retrieval based or Generative.
    1. In retrieval-based models, Chatbot uses the message and context of conversation for selecting the best response from a predefined list of bot messages.
    2. Generative bots can generate the answers and not always reply with one of the answers from a set of answers. This makes them more intelligent as they take word by word from the query and generates the answers.

 

Building a chatbot using Python

NLP:

The field of study that focuses on the interactions between human language and computers is called Natural Language Processing. NLP is a way for computers to analyze, understand, and derive meaning from human language in a smart and useful way. However, if you are new to NLP, you can read Natural Language Processing in Python.

 

NLTK:

NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use lexical resources such as WordNet, along with a suite of text processing libraries.

 

Importing necessary libraries

import nltk 

import numpy as np 

import random 

import string # to process standard python strings

 

Copy the content in text file named ‘chatbot.txt’, read in the text file and convert the entire file content into a list of sentences and a list of words for further pre-processing.

 

f=open('chatbot.txt','r',errors = 'ignore')

raw=f.read()

raw=raw.lower()# converts to lowercase

nltk.download('punkt') # first-time use only

nltk.download('wordnet') # first-time use only

sent_tokens = nltk.sent_tokenize(raw)# converts to list of sentences 

word_tokens = nltk.word_tokenize(raw)# converts to list of words

 

Pre-processing the raw text

We shall now define a function called LemTokens which will take as input the tokens and return normalized tokens.

 

lemmer = nltk.stem.WordNetLemmatizer()

#WordNet is a semantically-oriented dictionary of English included in NLTK.

def LemTokens(tokens):     

return [lemmer.lemmatize(token) for token in tokens]

remove_punct_dict = dict((ord(punct), None) for punct in string.punctuation) 

def LemNormalize(text):     

return LemTokens(nltk.word_tokenize(text.lower().translate(remove_punct_dict)))

 

Keyword matching

Define a function for greeting by bot i.e. if user’s input is greeting, the bot shall return a greeting response.

GREETING_INPUTS = ("hello", "hi", "greetings", "sup", "what's up","hey",)

GREETING_RESPONSES = ["hi", "hey", "*nods*", "hi there", "hello", "I am glad! You are talking to me"]

def greeting(sentence):

for word in sentence.split():

if word.lower() in GREETING_INPUTS:

return random.choice(GREETING_RESPONSES)

 

Generate responses

To generate a response from our bot for input queries, the concept of document similarity is used. Therefore, we start by importing necessary modules.

From scikit learn library, import the TFidf vector to convert a collection of raw documents to a matrix of TF-IDF features

from sklearn.feature_extraction.text import TfidfVectorizer

Also, import cosine similarity module from scikit learn library

from sklearn.metrics.pairwise import cosine_similarity

This will be used to find the similarity between words entered by the user and therefore the words within the corpus. This can be the simplest possible implementation of a chatbot.

Define a function response that searches the user’s vocalization for one or more known keywords and returns one of several possible responses. If it doesn’t find the input matching any of the keywords, it returns a response: “I’m sorry! I don’t understand you”

 

def response(user_response):

robo_response=''

sent_tokens.append(user_response)

TfidfVec = TfidfVectorizer(tokenizer=LemNormalize, stop_words='english')

tfidf = TfidfVec.fit_transform(sent_tokens)

vals = cosine_similarity(tfidf[-1], tfidf)

idx=vals.argsort()[0][-2]

flat = vals.flatten()

flat.sort()

req_tfidf = flat[-2]

if(req_tfidf==0):

robo_response=robo_response+"I am sorry! I don't understand you"

return robo_response

else:  robo_response = robo_response+sent_tokens[idx]

return robo_response

 

I have tried to explain in simple steps how you can build your own chatbot using NLTK and of course it’s not an intelligent one.

I hope you guys have enjoyed reading.

Happy Learning!!!

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