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New companies and the entrepreneurial impulse are key elements of the U.S. economy, and perhaps part of the nation’s mythology in the American dream. The U.S. federal agency in 2002 counted around twenty three million companies and nearly twenty four million business “establishments” that generated, in total, nearly $23 billion in sales. That’s if they make it. In a 2006 article entitled, “The Seven Pitfalls of Business Failure,” economic expert Brian Head of the small Business Administration noted that 30% new businesses fail inside the first five years of operation. However with careful coming up with, establishing a new company is a successful and profitable undertaking.

Steps for registering a new company

Choose your Company Location

Your company location determines the taxes, zoning laws, and regulations your company will be subject to. You will need to form a strategic decision regarding which state, city, and neighborhood you select to begin your company in. Where you locate your company depends in part on the location of your target market, business partners, and your personal preferences. In addition, you should consider the costs, benefits, and restrictions of different government agencies.

Choose right Company/Business type

The decision to choosing the right business structure is very important because the type of business you decide on influences everything from daily operations, to taxes, to how much of your personal assets are at risk.

  • Sole proprietorship: A sole proprietorship is easy to form and gives you complete control of your business. You're automatically considered to be a sole proprietorship if you do business activities but don't register as any other kind of business. Sole proprietorship do not produce a separate business entity. This means your business assets and liabilities are not separate from your personal assets and liabilities. You can be held personally liable for the debts and obligations of the business. Sole proprietors can also be hard to raise money because you can't sell stock, and banks are hesitant to lend to sole proprietorship.
  • Partnership: Partnerships are the best structure for two or more people to possess a business together. There are two common forms of partnerships: limited partnerships (LP) and limited liability partnerships (LLP).
    • Limited partnerships have only one general partner with unlimited liability, and all other partners have limited liability. The partners with limited liability also tend to have limited control over the company, which is documented in a partnership agreement.
    • Limited liability partnerships are similar to limited partnerships, but give limited liability to every owner. An LLP protects every partner from debts against the partnership, they won't be responsible for the actions of other partners.
  • Limited liability Company (LLC): LLCs protect you from personal liability in most instances, your personal assets like your vehicle, house, and savings accounts won't be at risk in case your LLC faces bankruptcy or lawsuits. Profits and losses can get passed through to your personal income without facing corporate taxes. LLCs can be a good choice for medium- or higher-risk businesses, owners with significant personal assets they want to be protected, and owners who want to pay a lower tax rate than they would with a corporation.
  • Corporation: The incorporation process is more complicated than the other two options but will have many potential benefits for your on-line business. One of the most notable differences regarding this structure is that the corporation becomes a separate entity from you as the owner. This means you’re not in person financially liable for what happens to the corporation, and your personal assets are protected from the liabilities created by your shop. When your store grows and the liabilities you’re exposed to grow with it this is a huge benefit.

Choose your Company Name

You can find the right business name with creativity and market research. Once you’ve picked your name, you should protect it by registering it with the right agencies.

You’ll want to decide on a business name that reflects your brand identity and doesn’t clash with the types of goods and services you provide. Once you take decision on a name you prefer, you would like to protect it. There are four different ways to register your company name. Every way of registering your name serves a special purpose, and some may be legally required depending on your business structure and location.

  • Entity name protects you at state level
  • Trademark protects you at a federal level
  • Doing Business as (DBA) doesn’t give legal protection, but might be legally required
  • Domain name protects your business web site address

Each of those name registrations are legally independent. Most small businesses try to use an equivalent name for each kind of registration, but you’re not commonly required to.

Register your Company

Register your business to make it a distinct legal entity. How and where you need to register depends on your business structure and business location.

Your location and business structure determine how you’ll need to register your business. Verify those factors first, and registration becomes terribly easy. In some cases, you don’t need to register at all. If you conduct business as yourself using your legal name, you won’t need to register anywhere. But keep in mind, if you don’t register your business, you'll miss out on personal liability protection, legal benefits, and tax benefits.

Most businesses don't need to register with the federal government to become a legal entity, other than simply filing to get a federal tax ID. Small businesses sometimes register with the federal government for trademark protection or tax exempt status. If you would like to trademark your business, brand or product name, file with the United States Patent and Trademark office once you’ve formed your business. If you would like tax-exempt status for a noncommercial corporation, register your business as a tax-exempt entity with the IRS.

Get Employee Identity Number or State Tax ID

Getting an EIN number can help you identify your business entity. Most companies need this federal employee identification number to conduct business. An EIN is a nine-digit number that refers to only your business or non-profit entity. It is your business’s social security number. This number allows the IRS to identify your business and attach it to the correct business name for tax purposes. Just a unique business name is not enough.

Your employer identification number (EIN) is your federal tax ID. You need it to pay federal taxes, hire employees, open a bank account, and apply for business licenses and permits. You should do it right once you register your business. Your business desires a federal tax ID number if it does any of the following:

  • Pays employees
  • Operates as an organization of partnership
  • Files tax returns for employment, excise, or alcohol, tobacco, and firearms
  • Withholds taxes on income, other than wages, paid to a non-resident alien
  • Works with certain types of organizations

The need for a state tax ID number ties directly to whether your business must pay state taxes. Sometimes, you can use state tax ID numbers for other functions, like protection against identity theft for sole proprietors. Tax obligations differ at the state and local levels, so you'll need to check with your state's websites. To know whether you need a state tax ID, research and understand your state's laws regarding income taxes and employment taxes, the two most common forms of state taxes for small businesses.

Apply for Licenses

Most small businesses need a combination of licenses and permits from both federal and state agencies. The requirements and charges vary based on your business activities, location, and government rules.

The licenses and permits you need from the state, county, or city will depend on your business activities and business location. Your business license fees will vary. States tend to regulate a broader range of activities than the centralized. As an example, business activities that are commonly regulated domestically include auctions, construction, and dry cleaning, farming, plumbing, restaurants, retail, and vending machines.

Some licenses and permits expire after a set period of time. Keep close track of when you need to renew them it's usually easier to renew than it has to apply for a new one. You'll have to analysis your own state, county, and city regulations. Industry requirements usually vary by state.

Special Bank Account for your Company

Open a business account once you are ready to start accepting or spending money as your business. A business bank account helps you keep legally compliant and protected. It also provides benefits to your customers and employees. Most business bank accounts provide perks that don't come with a standard personal bank account.

  • Protection: Business banking offers limited personal liability protection by keeping your business funds separate from your personal funds. Merchant services also offer purchase protection for your customers and ensures that their personal information is secure.
  • Professionalism: Customers will be able to pay you with credit cards and make checks out to your business instead of directly to you.
  • Preparedness: Business banking usually comes with the option for a line of credit for the company. This can be used in the event of an emergency, or if your business needs new equipment.
  • Purchasing power: Credit card accounts can help your business make large startup purchases and help establish a credit history for your business.

Get Business Insurance

Business insurance coverage protects businesses from losses due to events that may occur during the normal course of business. There are many types of insurance for businesses including coverage for property damage, legal liability and employee-related risks. Companies evaluate their insurance needs based on potential risks, which can vary depending on the type of environment in which the company operates.

Business insurance protects you from the unexpected costs of running a business. Accidents, natural disasters, and lawsuits could run you out of business if you’re not protected with the right insurance.

Speak to insurance agents to find out what kinds of coverage makes sense for your business, and compare terms and prices to find the best deal for you. Here are six common kinds of business insurance types are:

  • General liability insurance
  • Product liability insurance
  • Professional liability insurance
  • Commercial property insurance
  • Home-based business insurance
  • Business owner’s policy

NLP is a branch of data science that consists of systematic processes for analyzing, understanding, and deriving information from the text information in a smart and efficient manner. By utilizing NLP and its parts, one can organize the massive chunks of text information, perform various automated tasks and solve a wide range of issues like – automatic summarization, machine translation, named entity recognition, relationship extraction, sentiment analysis, speech recognition, and topic segmentation etc.

 

NLTK (Natural Language Toolkit) is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to lexical resources like WordNet, along with a collection of text processing libraries for classification, tokenization, stemming, and tagging, parsing, and semantic reasoning, wrappers for industrial-strength NLP libraries.

 

NLTK has been called “a wonderful tool for teaching and working in, computational linguistics using Python,” and “an amazing library to play with natural language.”

 

Downloading and installing NLTK

  1. Install NLTK: run pip install nltk
  2. Test installation: run python then type import nltk and run nltk.download() and download all packages.

 

Pre-Processing with NLTK

The main issue with text data is that it's all in text format. However, the Machine learning algorithms need some variety of numerical feature vector so as to perform the task. Thus before we have a tendency to begin with any NLP project we'd like to pre-process it to form it ideal for working. Basic text pre-processing includes:

 

  • Converting the whole text into uppercase or lowercase, in order that the algorithm doesn't treat the same words completely different in several cases.
  • Tokenization: Process of converting the normal text strings into a list of tokens i.e. words that we actually want. The NLTK data package includes a pre-trained Punkt tokenizer for English.

 

           import nltk

           from nltk.tokenize import word_tokenize

           text = "God is Great! I won a lottery."

           print(word_tokenize(text))

           Output: ['God', 'is', 'Great', '!', 'I', 'won', 'a', 'lottery', '.']

 

  • Noise removal: Process of removing everything that isn’t in a standard number or letter.
  • Stop word removal: A stop word is a commonly used word (such as “the”, “a”, “an”, “in”). We would not want these words or taking up valuable processing time. For this, we can remove them easily, by storing a list of words that you consider to be stop words. NLTK (Natural Language Toolkit) in python has a list of stopwords stored in sixteen different languages. You can find them in the nltk_data directory.  home/Saad/nltk_data/corpora/stopwords is the directory address.

           import nltk

           from nltk.corpus import stopwords

           set(stopwords.words('english'))

 

  • Stemming: Stemming is the process of reducing the words to its root form. Example if we were to stem the following words: “Connects”, “Connecting”, “Connected”, “and Connection”, the result would be a single word “Connect”.

           # import these modules

           from nltk.stem import PorterStemmer

           from nltk.tokenize import word_tokenize   

           ps = PorterStemmer()  

           # choose some words to be stemmed

           words = ["Connect", "Connects", “Connected”, "Connecting", "Connection", "Connections"]

 

           for w in words:

           print(w, " : ", ps.stem(w)) 

 

  • Lemmatization: Lemmatization is the process of grouping along the various inflected forms of a word in order that they may be analyzed as a single item. Lemmatization is similar to stemming but it brings context to the words. Therefore it links words with similar meaning to one word.

           # import these modules

           from nltk.stem import WordNetLemmatizer  

           lemmatizer = WordNetLemmatizer()  

           print("rocks :", lemmatizer.lemmatize("rocks"))

           print("corpora :", lemmatizer.lemmatize("corpora"))  

           # a denotes adjective in "pos"

          print("better :", lemmatizer.lemmatize("better", pos ="a"))

 

          -> rocks : rock

          -> corpora : corpus

          -> better : good

 

Now we need to transform text into a meaningful vector array. This vector array is a representation of text that describes the occurrence of words within a document. For example, if our dictionary contains the words {Learning, is, the, not, great}, and we want to vectorize the text “Learning is great”, we would have the following vector: (1, 1, 0, 0, 1). A problem is that extremely frequent words begin to dominate within the document (e.g. larger score), however might not contain as much informational content. Also, it will offer additional weight to longer documents than shorter documents.

 

One approach is to rescale the frequency of words or the scores for frequent words called Term Frequency-Inverse Document Frequency.

 

  • Term Frequency: is a scoring of the frequency of the word in the current document.

           TF = (Number of times term t appears in a document)/ (Number of terms in the document)

 

  • Inverse Document Frequency: It is a scoring of how rare the word is across documents.

           IDF = 1+log(N/n), where, N is the number of documents and n is the number of documents a term t has appeared in.

 

           Tf-idf weight is a weight often used in information retrieval and text mining.

           Tf-IDF can be implemented in scikit learn as:

 

           from sklearn.feature_extraction.text import TfidfVectorizer

           corpus = [

           ...     'This is the first document.’

           ...     'This document is the second document.’

           ...     'And this is the third one.’

           ...     'Is this the first document?',]

           >>> vectorizer = TfidfVectorizer()

           >>> X = vectorizer.fit_transform(corpus)

           >>> print(vectorizer.get_feature_names())

           ['and', 'document', 'first', 'is', 'one', 'second', 'the', 'third', 'this']

           >>> print(X.shape)

           (4, 9)

 

  • Cosine similarity: TF-IDF is a transformation applied to texts to get two real-valued vectors in vector space. We can then obtain the Cosine similarity of any pair of vectors by taking their dot product and dividing that by the product of their norms. That yields the cosine of the angle between the vectors. Cosine similarity is a measure of similarity between two non-zero vectors.

           Cosine Similarity (d1, d2) =  Dot product(d1, d2) / ||d1|| * ||d2||

 

          import numpy as np

          from sklearn.metrics.pairwise import cosine_similarity

          # vectors

          a = np.array([1,2,3])

          b = np.array([1,1,4])

          # manually compute cosine similarity

          dot = np.dot(a, b)

          norma = np.linalg.norm(a)

          normb = np.linalg.norm(b)

          cos = dot / (norma * normb)

 

After completion of cosine similarity matric we perform algorithmic operation on it for Document similarity calculation, sentiment analysis, topic segmentation etc.

 

I have done my best to make the article simple and interesting for you, hope you found it useful and interesting too.

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