Freelance Jobs

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 virtual assistant (VA) is a professional who provides administrative and support gigs. These can range from invoicing clients on a regular basis to managing a one-time project. Thanks to the wonders of email, instant messaging, conference calls, and video chat, your virtual assistant works remotely—he or she could be on the other side of the country, or even in another country—which means you don’t have to worry about finding additional office space.

Working from home, on your set schedule, from your own comfort, and earn more is not always as glamorous as it might seem. Becoming a Virtual Assistant it requires time and patience, along with some smart work. 

Assuming that you are clear with the basics of Virtual Assistant profession and know about the resources to find a Virtual Assistant services, let’s move on to how you can be more effective working as a Virtual Assistant.

How to become an Efficient Virtual Assistant?

Being an top professional Virtual Assistant is not rocket science and could be mastered with a little effort and patience. Given the high competition for these jobs, you need to stand out from your competition to land higher paying services.

Which basic skills make me a top virtual assistant?

Before you go on your virtual assistant journey, It is mandatory to make sure that you possess all the basic skills required. An ideal and successful virtual assistant would be on par with the basic skill-set required.

So do you think you have a good hold on the basic skills? Let’s go through a few basic skills expected by each client. Develope these skills and get hired today:

Comfortable with using Windows / Mac.

More than 45 words per minute.

Know how to use Internet and emailing.

Know the basics of social media marketing.

Have a good time and resource management skills.

Have a good understanding of newsletter creation.

Smartness

What should I do first to play experienced virtual assistant role?

Since 2007, virtual assistance has become a very in-demand field, and is seeing steady growth each year. With the numbers in mind, and the growing rate of business done online, it is no surprise that several virtual assistance companies have been born. These companies hire men and women from all across the world to work remotely and offer their clients the online support they need.

This is very good news for the brand new virtual assistant, because it means there are options for you to get a steady stream of work, steady paychecks, and professional support and training in the field. You can become a strong assistant very quickly, and then decide if you’d like to move up in the company or branch out on your own. Just be sure never to sign a non-compete agreement if you plan to eventually go it alone.

Learn about the basic ideas for the following term:

Customer Support

Processing Online Orders

Wordpress Maintainance

Keyword Research

Content Research

Email Management

Must have required tools for being a good virtual assistant

A right tool-set is a power in the hands of VA to build a legacy out of nothing. Make sure you have got nothing but the best tools before you jump in the market to play a solid role of virtual assistant.

A phone (cell or landline)

A good computer/laptop that works perfectly.

At least two up to date browsers.

A good email client.

Skype or other chat software.

A good speed Internet connection.

A perfect reminder device which tells or update you about your upcoming challenges.

These are just the basic tools required, and most of the people would mostly satisfy the criteria.

Can I work on fixed schedule as a Freelance Virtual Assistant

No matter you work locally or remotely, nothing is going to work for you if you neglect the importance of a fixed schedule. Although virtual assistant allows you flexibility from your home office, that doesn’t mean you wake up suddenly at the wake of the night and start working.

Make a habit of working during the same hours of the day, every day. You don’t need a 9-5 schedule, but a schedule is a must to get the most out of your work. Make a schedule as per the times when you are at your best with least distractions and day in day out, work during the same hours.

What strategy need to build?

If having a plan is good, having a plan B is a must. So, for every plan that you make, have an alternative plan ready to execute. Things might not always work out the way you planned them to, so having a backup plan will help you in the long run.

Build a strategy of how many hours you’re willing to work,

Where you’re going to work,

What about your taxes,

You should continue making a plan, and you will end up with more questions to be answered even before you accept your first service.

How to satisfy my customer’s as a virtual assistant?

Deliver more: When was the last time you over delivered and your customer couldn’t stop singing your songs? For customers to sing your song you need to provide that rare high-quality service. So it’s always good to deliver more, surprise your customers and keep them happy.

Don’t always do everything to earn more and at least sometimes do for the love of it. I love making people happy and go the extra mile to deliver more than anyone expects. Go out of your way to leave a legacy in whatever you do. Make people remember you for what you’ve done rather than as a man who’s always bugging about the next paycheck.

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.