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Top 26 Machine Design Freelancers on 17 Jun 2019 on Toogit. Machine Design Freelancers on Toogit are highly skilled and talented. Hiring Machine Design Freelancers on Toogit is quite affordable as compared to a full-time employee and you can save upto 50% in business cost by hiring Machine Design Freelancers on Toogit. Hiring Machine Design Freelancers on Toogit is 100% safe as the money is released to the Freelancer only after you are 100% satisfied with the work.

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# Fashion M.Fashion designer, India
/hr
0 Years Exp.
0 Followers
I am 17years old I am making fashion illustrations of kids women and men I have no experience I have no degree The purpose is just to tell my tal...Read More
Ghita S.dietetician nutritionist , Morocco
$4 /hr
1 Years Exp.
0 Followers
I am in the first nutrition dietetics studies, I am looking for online jobs, I'm a fast learner, I write in my free times.
Manideep B.Textile print Designer, India
$3 /hr
0 Years Exp.
0 Followers
I am a graphics Designer, having experience of 2 years in Textile print Designing.
Chadeaux Creative Designer and Fashion Illustrator , Jamaica
$8 /hr
0 Years Exp.
0 Followers
I am a self taught Jamaican artist. I am a creative at heart and and best at traditional graphic designing. I have a good fashion sense as well, and...Read More
Derique Derique Fashion designer , Kenya
$25 /hr
2 Years Exp.
1 Followers
I am an experienced fashion designer with 6 years on the field,having managed to dress some of the popular local artists and also models . I am also q...Read More
Andrea Belludo Fashion and Textile Designer, Philippines
$15 /hr
7 Years Exp.
0 Followers
For over 7 years, I have created high-end fashionable and functional designs for international clients and was able to conduct fashions shows for the...Read More
Aditi S.A keen learner and explorer. , India
$6 /hr
1 Years Exp.
0 Followers
I am pursuing B. Des. In fashion designer. I would savour to work in illustrations, graphic design, editorials, costume design.
Chhavi P.Fashion Designer, India
$9 /hr
1 Years Exp.
0 Followers
I am a fresher Fashion Design Graduate from National Institute of Fashion Technology. With passion for designing I also have an interest in writing as...Read More
Anmol G.Fashion designer , India
$34 /hr
2 Years Exp.
0 Followers
I am gud in fashion illustrations sketch, women clothing designing,
Tanya G.fashion designing, India
$3 /hr
1 Years Exp.
0 Followers
i have done professional diploma in fashion designing and ethnic wear + i am 1.5 year experienced as assistant designer
Nishtha G.fashion designer /fashion stylist, India
$17 /hr
2 Years Exp.
0 Followers
i am certified in fashion designing course minimum 3 yr and i experienced 1-2 yr as a freelance in fashion designing and fashion styling.
Anjali A.System engineer, India
$3 /hr
2 Years Exp.
0 Followers
I am a java developer having 2 years of experience. Looking for work from home job just go earn little more. I have dedicated mind. Decide.commit.succ...Read More
Lisco L.Journalist, Namibia
$15 /hr
9 Years Exp.
0 Followers
I am a Namibian journalist with up to nine years’ experience as a news reporter, subeditor and editor. My most recent work in the media field was for...Read More
Tamanna Thakur Fashion designer , India
$17 /hr
2 Years Exp.
0 Followers
I am a fashion designer cum merchendiser. I have 2years of experience in adobe
Gazal K.Content writer, India
$4 /hr
0 Years Exp.
0 Followers
I am a freelance writer. Even though i am a fresher with lack of experience i do pretty well with my articles on social media. Social media is my fort...Read More
Shanaya C.Analyst, India
$17 /hr
0 Years Exp.
0 Followers
Iam a student, interested to do some part-time work.
Geeta Work as fashion designer , India
/hr
5 Years Exp.
0 Followers
I am certified as cad instructor as well as a fashion designer for 5+ years, in sagar fashion studio in Mumbai Maharashtra.
Ashna A.Fashion designer, print desingner, India
$12 /hr
2 Years Exp.
0 Followers
I did my graduation from National Institute of Fashion Technology (NIFT). I have one year of experience at Sai export house for print designing. I did...Read More
Ammarah Copy Typing , India
$2 /hr
0 Years Exp.
0 Followers
Currently I am student studying Bcom IFA in collaboration with ACCA. I have completed my diploma in fashion designing from Hamstech institute of fash...Read More
Sharmili M.Textile ArtistI , India
$9 /hr
0 Years Exp.
0 Followers
I am a keen aspirant in the field of fashion, textiles , art and design. I look forward to work in these areas to enhance relevant skills and m.ove f...Read More
Raphael S.Fashion designer, India
/hr
1 Years Exp.
0 Followers
High on Creativity and artistic, Excellent Drawing, storng visualization skills, Happy to take challengees work
Oluwasijibomi O.HEAD TELLER SERVICES, Nigeria
$15 /hr
8 Years Exp.
0 Followers
I hold a degree in Actuarial science and I have been working in a bank for the past six years.
Abir graphic designer, Morocco
$5 /hr
2 Years Exp.
0 Followers
i am an engineering student with multiple skills, i am good with adobe photoshop and adobe illustrator, i speak 4 languages: english, spanish, arabic...Read More
Shweta Fashion Designer, Illustrator, India
$25 /hr
3 Years Exp.
0 Followers
Hi, I'm a qualified Fashion Designer and have experience in Fashion Designing & Illustrations.
Thameeza N.Fashion illustrations, India
$9 /hr
1 Years Exp.
0 Followers
Iam Thameeza, a costume designer. Iam graduated in BSC costume design and fashion. I have experience in this field. And also a portrait drawings artis...Read More
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Skills related to Machine Design

Articles Related To Machine Design


The global demand for data Science professionals is extremely high because of increasing relevance across various sectors. Data Science has become the most-sought skill because the data is piling along with a surge in different tech fields like Artificial Intelligence, machine learning and data Analytics. Hiring data scientist is being carried across numerous domains like e-commerce, education, retail, telecommunication and much more.

 

In the past years, analysts used excel tools to analyze data. Things are changing now! In this modern world, data-driven decision making is sparkling and technology is advanced in the data industry. The tools and technologies that modern Data Scientists employ are a combination of statistical and Machine Learning algorithms. They are used to discover patterns using predictive models. The future of Data Science is bright and the options for its implementation are extensive.

 

Data Scientists must consistently evolve at the edge of innovation and creativity. They must be aware of the types of models they create. These innovations will allow them to spend time discovering new things that may be of value. Subsequently, the advances in Data Science tools will help leverage existing Data Science talent to a greater extent.

 

So what does a Data Scientist do?

Data Scientists influence a pile of data in an innovative way to discover valuable trends and insights. This approach helps to identify opportunities by implementing research and management tools to optimize business processes by reducing the risks. Data Scientists are also responsible for designing and implementing processes for data mining, research and modeling purposes.

 

Data scientist performs research and analyses data and help companies flourish by predicting growth, trends and business insights based on a large amount of data. Basically, data scientists are massive data wranglers. They take a vast data and use their skills in mathematics, statistics and programming to scrub and organize the information. All their analysis combined with industrial knowledge helps to uncover hidden solutions to business challenges.

 

Generally, a data scientist needs to know what could be the output of the big data he/she is analyzing. He/she also needs to have a clearly defined plan on how the output can be achieved with the available resources and time. Most of all the data scientists must know the reason behind his attempt to analyze the big data.

 

To achieve all of the above, a data scientist may be required to:

 

Every organization has unique data problems with its own complexities. Solving different Data Science problems requires different skill sets. Data Science teams are groups of professionals with varied skill sets. They, as a team, solve some of the hardest data problems an organization might face. Each member contributes distinctive skill set required to complete a Data Science project from start to finish.

 

The Career Opportunities:

The careers associated with data science are generally categorized into five.

 

  1. Statisticians: Statisticians work usually for national governments, marketing research firms and research institutes. Extracting information from massive databases through numerous statistical procedures is what they do.
  2. Data Analyst: Telecommunication companies, manufacturing companies, financial companies etc. hire data scientists to analyze their data. A data analyst keeps track of various factors affecting company operation and make visual graphics.
  3. Big Data and Data Mining Engineer: Tech companies, retail companies and recreation companies use data scientists as data mining engineers. They have to gather and analyze huge amounts of data, typically from unstructured information.
  4. Business Intelligence Reporting Professional: They work for tech companies, financial companies, and consulting companies etc. Market research is the primary objective of this job. They also generate various reports from the structured data to improve the business.
  5. Project Manager: A project manager evaluates data and insights fetched from the operational departments and influences the business decisions. They have to plan the work and make sure everything goes in accordance with the plan.

Python and Java both lay claims to being among the top five most popular programming languages at any given time, with Java usually just ahead of Python. However, Python’s popularity is growing at a tremendous rate, and Python overtake Java in 2018.

 

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python was designed to be highly readable which uses English keywords frequently whereas other languages use punctuation and it has fewer syntactical constructions than other languages.

 

Java and Python have many similarities. Both languages have strong cross-platform support and extensive standard libraries. They both treat (nearly) everything as objects. Both languages compile to bytecode, but Python is (usually) compiled at runtime.

 

Python versus Java:

  1. Java language is more about syntax, if one can forget to add curly braces or semicolon in the end then this will show error as your output. But there is nothing like that with python there is no need of semicolon and curly braces in the end but python follows indentation process so that it will make your code readable.
  2. Java programming is statically typed means that one has to explicitly mention the data type of variable. If datatype (int, float, double, character) isn’t mentioned then the error can occur in program. Python is dynamically typed means if one has directly assigned a value to a variable at the runtime then it'll assume data type.
  3. Java codes are more complex than python codes. Try to write a hello world program in both then you'll observe the complexness of the code, four lines of code in Java and same hello world program in python are of 1-line code.
  4. Python has a large and robust standard library makes Python score over other programming languages. The standard library allows you to choose from a wide range of modules according to your precise needs. Each module further enables you to add functionality to the Python application without writing additional code.
  5. Python is an open source programing language, Python helps you to curtail software system development cost significantly. You’ll even use many open source Python frameworks, libraries and development tools to curtail development time without increasing development cost. You even have choice to select from a wide range of open source Python frameworks and development tools per your precise needs.
  6. Interpreted, with tools like IDLE, you can also interpret Python instead of compiling it. While this reduces the program length, and boosts productivity, it also results in slower overall execution.
  7. Python is considered to be the most favorable language for Machine Learning, Artificial Intelligence, IoT and much more.
  8. Python has a more unified support model than Java for the first time, and open source developers are focusing their efforts on the latest version of the language.
  9. After working on large projects in both languages, I feel secure saying that Python’s syntax is more concise than Java’s. It’s easier to get up and running quickly with a new project in Python than it is in Java.
  10. The most two popular frameworks for Python are Django and Flask. Flask is a micro web framework, it gives you the basic functionalities you’d need like routing requests without much overhead. Django is a more featured option and can help you build a powerful backend while capitalizing on efficiency and security, Django is equipped with a powerful ORM layer which facilitates dealing databases and performing different operations on the data.

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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