Trending February 2024 # How To Perform Boom Arena Glitch? # Suggested March 2024 # Top 9 Popular

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Boom Arena is a popular MOBA-like brawler game with a deck builder system in it.

However, like every other game, currently, the game has an exploit as well.

Players of Boom Arena are currently using an exploit to earn easy victories. Furthermore, a few players are also showcasing how to pull it off. However, the Boom Arena Glitch is not as easy as it seems and is very different to pull off between Android and IOS platforms.

Continue reading to learn how to pull off the Boom Arena Glitch on Android and IOS.

What Is Boom Arena?

Boom Arena is a free MOBA-like brawler game with deck-builder elements.

The game allows players to build a set deck of characters according to the player’s liking.

Furthermore, the game seems to take inspiration from popular games like Hearthstone, a popular card game and some MOBA elements from games like DOTA 2 and League of Legends.

Moreover, the game also contains many Real Time Strategy elements like Warcraft and Starcraft, to name a few.

However, the game shares the most uncanny resemblance to games like Clash of Clans and ClashRoyale.

What Is Boom Arena Glitch?

Currently, players can exploit a major Glitch in Boom Arena.

This Glitch allows the players to spawn their troops directly over the king tower in the game.

It results in the players unfairly winning the game.

However, due to many players exploiting this Glitch, the developers of Boom Arena will be patching this Glitch soon.

How To Perform Boom Arena Glitch?

Players on different platforms need to perform the Glitch in different manners.

Furthermore, since the game is only available on Android and IOS, players must look at two methods of performing the Glitch.

Perform Boom Arena Glitch On Android

In Android players must perform a few tasks before performing the Glitch.

Here is a list of steps to follow to perform the Glitch in Boom Arena for Android Users;

Players must have enough elixir for the card they want to teleport to the king.

Then, they must hover a spell, faun barrel or digger over the enemy King tower. However, do not let go of the card, this is the major step for the Glitch.

    Finally, while hovering over the previous card on top of the king tower, choose the card you want to teleport over the king.

    After performing this Glitch, your characters will spawn over the king tower and destroy within seconds. Thus, you will end up a victor.

    For better clarification on how to perform the Glitch on Android here is a video from one of the players performing the Glitch.

    Perform Boom Arena Glitch On IOS

    Like Android, the players must perform a few tasks before performing the Glitch.

    Here is a list of steps to follow to perform the Glitch in Boom Arena for IOS users;

    First, choose any spell you want from your deck.

    Then, unfocus the application for a second while holding the spell.

    Finally, tap any card you want to teleport over the king tower.

    Furthermore, players also claim that the assistive touch helps make this Glitch work much better for some players.

    For better clarification on how to perform the Glitch on IOS here is a video from one of the Reddit users performing the Glitch.

    The Bottom Line

    Boom Arena is quite popular getting 4.5 stars in the play store. However, Glitches like this can cause that great rating to fall off.

    Furthermore, due to a few uproars from the community showcasing this Glitch, chances are the developers are working on a fix for the Glitch.

    Hopefully, this article can help you perform the Glitch and get a few easy victories under your belt.

    You're reading How To Perform Boom Arena Glitch?

    How To Perform String Comparison In Typescript?

    In this TypeScript tutorial, users will learn to make string comparisons. The string comparison is the basic operation required while working with any programming language.

    Suppose we are developing a web or Android application and need to compare string data such as user id, user name, password, etc. In such cases, string comparison becomes very useful.

    Using the strict equality (===) operator

    The best way to compare the strings in TypeScript is to use the strict equality operator. The strict equality operator first checks the types of the left and right operands, and if it matches, it compares the value of the string and returns the boolean value based on the match of the string.

    Users can follow the syntax below to compare the strings using the strict equality operator in TypeScript.

    Syntax let string1: string = " "; let string2: string = " "; let value: boolean = string1 === string2;

    In the above syntax, we have created the two strings and compared them using the strict equality operator.

    Steps

    STEP 1 − Create two different strings – ‘string1’, and ‘string2’.

    STEP 2 − Assign the comparison result of ‘string1’ and ‘string2’ into the ‘value1’ boolean variable.

    STEP 3 − As a final step, we print the value of ‘value1’. If the value of ‘value1’ is ‘true’ then the strings are ‘equal’ else, they are ‘not equal’.

    Example 1

    In the example below, we compare two strings- string1 and string2. We have taken both strings as the same, so we expect the output to be ‘true’.

    let string1: string = "TutorialsPoint"; let string2: string = "TutorialsPoint"; let value1: boolean = string1 === string2; console.log(value1);

    On compiling, it will generate the following JavaScript code −

    var string1 = "TutorialsPoint"; var string2 = "TutorialsPoint"; var value1 = string1 === string2; console.log(value1);

    The above code will produce the following output −

    Output true Example 2

    In the example below, we compare two strings- string1 and string2. We have taken both strings as different, so we expect the output to be ‘false’.

    let string1: string = "TutorialsPoint"; let string2: string = "Tutorial"; let value1: boolean = string1 === string2; console.log(value1);

    On compiling, it will generate the following JavaScript code −

    var string1 = "TutorialsPoint"; var string2 = "Tutorial"; var value1 = string1 === string2; console.log(value1);

    The above code will produce the following output −

    Output false Using the strict equality operator to do case-insensitive string comparison

    Sometimes, we require to compare the string case-insensitively. The case-insensitive string comparison means all characters of both strings are the same but not the case for all characters of strings.

    Users can follow the syntax below to compare the strings case-insensitively.

    Syntax let string1: string = "TUTORIALSPOINT"; let string2: string = "tutorialspoint"; let value1: boolean = string1.toLowerCase() === string2.toLowerCase(); let value2: boolean = string1.toUpperCase() === string2.toUpperCase();

    First, we have converted the strings to lowercase in the above syntax and compared them. Also, we have converted the strings in uppercase and compared them.

    Steps

    STEP 1 − Create two strings – ‘str1’ and ‘str2’, containing the same value but with different cases. 

    STEP 2 − Next, convert the ‘str1’ and ‘str2’ to lowercase, or uppercase.

    STEP 3 − Compare them using the strict equality operator, and stored its result in the `val1` boolean variable.

    STEP 4 − In the last step, we are also printing the value of the `val1`.

    Example

    To compare the strings case-insensitively, users can simply convert both strings into lowercase or uppercase and compare them. In the example below, we compare two strings containing the same value but with different cases.

    let str1: string = "TUTORIALSPOINT"; let str2: string = "tutorialspoint"; let val1: boolean = str1.toLowerCase() === str2.toLowerCase(); let val2: boolean = str1.toUpperCase() === str2.toUpperCase(); console.log("After converting both strings into the lowercase, comparison result is : " + val1); console.log("After converting both strings into the lowercase, comparison result is : " + val2);

    On compiling, it will generate the following JavaScript code −

    var str1 = "TUTORIALSPOINT"; var str2 = "tutorialspoint"; var val1 = str1.toLowerCase() === str2.toLowerCase(); var val2 = str1.toUpperCase() === str2.toUpperCase(); console.log("After converting both strings into lowercase, comparison result is : " + val1); console.log("After converting both strings into uppercase, comparison result is : " + val2);

    The above code will produce the following output −

    Output After converting both strings into lowercase, comparison result is : true After converting both strings into uppercase, comparison result is : true

    In the above output, users can see that value of the ‘val1’ and ‘val2’ is true as we are comparing both strings after converting into the same case, either lowercase or uppercase.

    Using the loose equality (==) operator

    Also, users can use the loose equality operator (==) to compare the strings. It will also give the same result as the strict equality operator gives, and it is the main benefit of TypeScript over JavaScript. Users can follow the Example below to compare the strings using the loose equality operator.

    Example

    In the below Example, users can see that we are comparing the ‘str1’ and ‘str2’ using the loose equality operator.

    let str1: string = "Hello"; let str2: string = "World!"; let val1: boolean = str1 == str2; console.log(val1);

    On compiling, it will generate the following JavaScript code −

    var str1 = "Hello"; var str2 = "World!"; var val1 = str1 == str2; console.log(val1);

    The above code will produce the following output −

    Output false

    Users learned to compare the strings in this tutorial. Unlike JavaScript, the strict and lose quality operator works the same for the string comparison as we define the data type of variables in TypeScript, and it doesn’t allow us to compare the variables of different data types.

    How To Perform Sas Upcase With Function And Character?

    Introduction to SAS Upcase

    The SAS Upcase is one of the default functions. It performs the copy operation under the character expression, which helps convert the lowercase letters to uppercase letters and return the result value. Also, it validates the string characters, like whether it contains them or not; the dataset helps to differentiate the table rows and columns, which includes the blank space on each set of characters.

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    Key Takeaways

    It converts the lowercase letters into upper case letters.

    It can also omit the spaces and delimiter if the SAS inputs change.

    The string is the parameter or arguments in the UPCASE(string) method.

    If the user inputs Uppercase’s first character, the other characters are lowercase. By using this method, the rest of the characters are changed to uppercase.

    So inputs are calculated and distinguished with characters on each string word.

    What is SAS Upcase?

    SAS Upcase is one of the default functions and performs the copy operations to convert lowercase characters to uppercase. It helps copy the character expression and related areas like variables, operators, and other things like numbers. The Upcase(expression) method is specified with the valid set of expressions concerned with the string character so that it will convert the lowercase letters to uppercase letters with return the altered values. Macro will convert to Uppercase, which is accomplished using the UPCASE() function that takes up the argument as converted uppercase.

    SAS Upcase Function

    The upcase() is also the macro function that can convert the text to upper-case, which is already in the lowercase of letters. We can use the same process for converting the string variable to the upper case and by using the datastep for data imported successfully. Character functions are most frequently used in the SAS, comparing the string to numeric values. Like that, COMPBL is the function for comparing the multiple blanks into the single blank data containing the single set of records; it occurs in the various spaces from the first and last strings. To make a string variable’s letters in all the uppercase characters by using the STRIP function to remove the leading and trailing spaces for all the areas, like the first and last names of the strings.

    SAS Upcase Character

    a is the modifier to remove the upper and lower characters from the strings.

    kd is the numeric set of values from the modifier.

    d is the numerical values removed from the string modifier.

    I is used to removing the upper and lower case strings.

    k is also specified string characters that keep instead of the existing one.

    Similarly, p is the punctuation mark that can be used between the first and last character strings. Omit the space and change the delimiter on the SAS strings. S is a modifier that removes the string spaces with the default one, and U is the string character that drew the uppercase only from the specified characters.

    How to Perform SAS Upcase?

    Given below shows how to perform SAS Upcase:

    1. Navigate to the below URL and log in to the application.

    3. And paste the below code for creating the dataset.

    4. data work.August15;

    5. input string $ 0-9;

    6. datalines;

    7. Welcome To

    8. My Domain January

    9. a February March

    10. THe April May

    11. ;

    12. run;

    13. We need to perform the Upcase operation in the above dataset. Using the upcase() method, we can pass the parameter arguments like a string in the method below.

    SAS Convert to Upcase

    The SAS upcase function is mainly used to convert the string character into the uppercase character, passing the string as the function argument. It includes the English alphabet letters, characters, and symbols, which can be called the altered way approach for returning the values. We can remove unwanted spaces, characters, strings, and other variables.

    To achieve the upcase function in the SAS processes, we used the input() function to get the user input as the character, so we used the upcase() function to convert the lowercase letters to uppercase. If we used input as the number format, it would omit and reuse the characters also, the decimal format of the input character is calculated additionally, the floating-point of the system is referred to as Width and Decimal, which call it as W.D, can be used in the proper way of the system and right places.

    Example of SAS Upcase

    Given below is the example mentioned:

    Code:

    data August15; input vars $0-9; datalines; January February March april May june July august September october November december ; run; proc print data=August15; data Augustne; set August15; vars = UPCASE(vars); run; proc print data=Augustne;

    Output:

    Explanation:

    1. The above example created the dataset and performed the upcase operation in the mentioned SAS user inputs.

    3. Initially, we can set the dataset data in the second case.

    4. Finally, the upcase function is executed and shows the same results.

    FAQ

    Given below is the FAQ mentioned:

    Q1. What is SAS upcase?

    Answer:

    It is one of the default SAS methods, and it is used to convert the lower case characters into upper case characters.

    Q2. How to use the upcase() in SAS?

    Answer:

    When we use the upcase() function, which can take only the strings and that will be the excellent case, like the first character of the input is in uppercase and the rest of the characters are in lowercase, etc.

    Q3. Will SAS upcase() omit the special characters in the user inputs?

    Answer:

    Yes SAS upcase() method omitted the special characters like operators, expressions, and other symbols in the inputs.

    Conclusion

    The SAS upcase() function is the default one, converting the user inputs from lowercase characters into uppercase letters. It includes the alphabet, not symbols, characters, operators, and other symbols. Every first character of the input words is Uppercase, and the rest of the characters are in lowercase is the condition for validating and performing the upcase function in SAS.

    Recommended Articles

    This is a guide to SAS Upcase. Here we discuss the introduction, function, character, how to perform SAS upcase, example, and FAQ. You may also have a look at the following articles to learn more –

    How To Perform The Ultimate Seo Content Audit For Your Blog

    It seems that the more posts you make to your blog, the more traffic you will receive. The more content you provide to your blog, the more likely readers will discover it through various channels like search engines, social media, and word-of-mouth.

    Not every time, though.

    It’s easy for your finest articles to get stale as you crank out new content. There’s always the chance that some articles will just “get buried.” When there are hundreds of updates to browse, even the greatest and most interesting ones may get lost in the shuffle.

    An SEO content audit is designed to help you straighten things out and keep your blog and its content in tip-top form.

    While “SEO content audit” may sound ominous, there’s nothing to worry about. The procedure entails performing a comprehensive blog audit, during which you will inventory your blog’s material, conduct optimization work, and, if necessary, repurpose that content.

    Don’t worry if that’s too cryptic for you. As a result, we’re going to dissect the entire procedure. Your education toward (blog) auditing certification will be complete by the time you finish reading this article.

    A Content Audit: What Is It?

    A content audit thoroughly examines all of your site’s written materials. The goal is to improve your content plan by adjusting your content strategy and content generation workflow to meet your current marketing objectives. Companies of all sizes, from startups to multinationals, can benefit.

    In this tutorial, I’ll show you the five most important ways to examine your material for errors −

    To begin, you must establish what success looks like.

    Second, you’ll need to conduct a content audit.

    Third, you’ll need to gather and analyze data.

    Fourth, you’ll need to create a strategy for moving forward.

    Lastly, Modify Your Content Promotion Approach

    Step 1: Establish Your Objectives

    Given the effort required for a content audit, it’s crucial first to establish what it is you hope to achieve.

    You need to choose one overarching objective to serve as the audit’s linchpin before settling on the metrics by which its success will be judged. It’s possible that these things could include −

    Boosting search engine optimization (SEO) for one page or site.

    boosting activity and/or sales.

    Getting rid of old or unnecessary material.

    Raising the quality of previously published works.

    Establishing a brand-new site hierarchy.

    Step 2: Collect & Categorize

    The next step is to list everything you plan on reviewing before you start compiling a list of URLs and metrics. Blog articles, news, educational materials, product descriptions, and landing pages are all examples of internal content that can be audited, as can external publications. Video, PDFs, and interactive content like quizzes, tests, and games can also be evaluated.

    Here, we’ll look at how to audit your website’s written content.

    URL.

    Author.

    Who created it? The Content Team, Social Media Team, Search Engine Optimization Group, etc.

    How long did it take to create the full piece?

    Title.

    Date.

    Is it an infographic, a case study, a blog piece, or something else entirely?

    Why did you make this piece of content? Were you hoping to get more backlinks, visitors, customers, or anything else?

    Consider the word count.

    Comments.

    Provide a breakdown of the share count in social media platforms and overall terms.

    Step 3: Analyze the Data from Your Blog

    Perhaps you’re wondering, “What exactly are analytics?” Search engine optimization analytics software lets you monitor and analyze the number of visitors to your site. Many tools provide different levels of insight, so your chosen one should be based on your goals.

    Now is the time to see what your analytics system tells you based on the data you’ve been collecting. The following are some of the things we’d like to double-check during an SEO content audit −

    Has there been any unexpected movement in traffic during the past few weeks or months?

    Ranking drops relative to the previous content audit

    How have conversion rates changed over the previous few months?

    Substantial shifts in user engagement metrics since the last content audit

    An SEO content audit can help you compile all this data into a cohesive whole from which you may draw more precise conclusions. Articles that aren’t doing well, pages that require more SEO work, and more may all be easily identified.

    Step 4: Draw An Action Plan

    Now that you know what constitutes quality, you can stop taking a bird’s-eye view of your blog and start evaluating each post on its merits.

    We’ll suggest each post using the information we’ve gathered and processed. It is also suggested that you provide a brief justification for each recommendation if you need a client’s or boss’s permission to implement the suggested alterations. In this step, you must decide which content to keep, update or delete.

    Step 5: Tweak Your Content Promotion Techniques

    Keep your website’s long-term marketing goals in mind when you conduct a content audit. If you keep tabs on what works and what doesn’t, you can alter your content strategy to reach your audience better, boost your organic traffic, and increase your conversion rates.

    Learn from success and build upon it. Look at your least successful material, and evaluate your competitors’ equivalent successful content to discover where and how you could enhance yours.

    At the very least, you should evaluate how well your content marketing approach achieves your stated objectives annually. It’s important to schedule regular reviews, such as once a month or every quarter, but more frequent intervals may be necessary if your industry is dynamic. You must adapt to these shifts and use creative approaches to maintain your audience’s attention and participation.

    What works now may not work tomorrow, so it’s important to make adjustments regularly. At least twice a year, you should conduct a content audit to assess the efficacy of your changes and overall strategy.

    Conclusion

    Indeed, content audits are not the most exciting aspect of marketing, but they are crucial. Remember that even the most successful of your articles may become obsolete in a matter of days. Auditing Regularly is necessary to ensure your efforts pay off. It’s the most thorough method for monitoring your site’s performance. It will also help you recognize fresh chances and attain your goals.

    Shiny Pokemon Go Hunting Glitch Discovered At Last

    Shiny Pokemon GO hunting glitch discovered at last

    There’s a bit of a glitch in Pokemon GO that’s not a big enough deal for Niantic to “fix”. This glitch is nicknamed “Skip Catch”, and it’s pretty much exactly what you’d expect – it skips the lengthy process of waiting for each Pokemon to wiggle around and either escape or remain in your care forevermore. You’re going to need two hands to do this method, which is a bit of work, but it’s worth the effort if you’re looking for Shiny Pokemon en masse.

    The Shiny Pokemon hunt in Pokemon GO rages on! After thousands of catches and dozens of Shiny Pokemon – dozens! – the strategy remains largely the same. Catch as many of one Pokemon as you can, and provided there IS a Shiny of said Pokemon, a shiny you may find! To make this method slightly less maddening that it inevitably turns out to be, the Skip Catch glitch is key.

    NOTE: The image at the top of the article was sorta vandalized by SlashGear (in a positive, supportive way!) And was originally illustrated by Sarah Richford. More information on this stack of Mudkips can be found at the Sarah Richfords DeviantArt page.

    To make this Skip Glitch action yours, you’ll need to follow the following instructions in either the Android or iOS version of Pokemon GO. Make sure you’re seeking out a Pokemon that actually has a Shiny version in the game before you use this method 12,000 times, if you’re looking specifically for Shinies, but feel free to use the method for whatever sort of Pokemon you like – it’s good for all! The instructions are followed by a helpful instructional video from the folks at BitRulez.

    • Step 1: In a Pokemon encounter, swipe over your Pokeball, right to left, and keep your finger on the screen (don’t lift up yet!)• Step 2: Throw the Pokeball with your free hand (like normal) while keeping your Step 1 finger pressed on the screen.• Step 3: Once the Pokeball has hit the Pokemon (Nice!) you’ll remove your Step 1 finger from the screen.• Step 4: As the Pokemon is being kidnapped by the Pokeball, you should see your drawer full of Pokeballs jump out from the right side of your display.• Step 5: Tap your display once.• Step 6: Tap your escape button (run away) in the upper left-hand corner of your screen.• Step 7: Repeat at will. If you captured the Pokemon, you’ll see some sort of ERROR message (don’t worry, nothing bad happened to you or your Pokemon). Otherwise you can try again!

    If you captured the Pokemon successfully, you’ll likely find an ERROR 55. If you did not, you’ll be given the opportunity to move in and out of the capture screen far more quickly than you’d have gone without the Skip Catch method. Have a peek at the timeline below and prepare your mind and your soul to capture as many Mudkips as possible in July. The big event is nearly here, and a Shiny Mudkip shall be yours.

    A Guide To Perform 5 Important Steps Of Nlp Using Python

    This article was published as a part of the Data Science Blogathon

    Natural Language Processing is a popular machine learning technique used to analyze t content. We see a lot of fancy reports around us and a lot of companies use business intelligence insights to drive their business. Most of these insights and reports are created using structured data. There are still some use cases for unstructured data. These could be in the form of text, tweets, images, etc. NLP focuses on bringing out meaningful insights from these text-based sources.

    Some examples of NLP include sentiment analysis. So if you have a company and have newly launched a product, you can analyze the sentiments of the users via their tweets. Even product reviews on your website can be analyzed in the same way.

    Challenges of NLP

    So what seems to be the challenge here?

    Let us take an example of a review: “The product is extraordinarily bad”

    Extraordinary is usually referred to in a positive way. If we were to use a keyword-based approach and tag it using the word extraordinary, then it would be incorrect. This is where NLP comes in. These situations where oxymorons are used need to be handled carefully.

    Another challenge is in terms of similar words as well as ambiguous meanings.

    Irony and sarcasm is difficult for a machine to understand

    Advantages of NLP

    Can work with unstructured data.

    More insights on the sentiments of a customer.

    Chatbots and other such AI/ML-based devices/technologies are being improved upon.

    Steps involved in NLP

    Let us take a look at the basic steps involved in running a simple NLP algorithm using a news article dataset.

    I have imported the required libraries for this data processing using NLP. Post that I have imported the file from my local system

    import gensim import numpy #numpy.numpy.random.bit_generator = numpy.numpy.random._bit_generator from gensim.utils import simple_preprocess from gensim.parsing.preprocessing import STOPWORDS from chúng tôi import WordNetLemmatizer, SnowballStemmer from nltk.stem.porter import * import numpy as np np.random.seed(2024) import nltk nltk.download('wordnet') import pandas as pd data = pd.read_csv('C:UsersktkDesktopBBC News Test.csv', error_bad_lines=False); data data_text = data[['Text']] data_text['index'] = data.ArticleId documents = data_text Tokenization

    This is the first major step to be done to any data. So what does this step do? Imagine you have a 100-word document. You need to split the document into 100 separate words in order to identify the keywords and the major topics. This process is called tokenization. I have used an example where I have imported the data sets and used a gensim library for all the preprocessing steps.

    This library has a preprocess function that helps tokenize the keywords. I have used a function called preprocess to help pick out the keywords. Different libraries have different functions for this process.

    processed_docs = documents['Text'].map(preprocess) processed_docs[:10]

    You can also remove the punctuation in this same step. There are functions for the same as well. Since this particular dataset does not have any punctuation, I have not used the punctuation removal functions.

    Stop Word Removal

    You have a huge dataset or several articles. In these articles, you will find that a lot of words like, “is”, “was”, “were”, etc are present. These words do not technically add any value to the main topic. These are tagged as stop words. There are a number of stop word removal techniques that can be used to remove these stop words. This will help us to arrive at the topic of focus.

    import nltk from nltk.corpus import stopwords print(stopwords.words('english')) stop_words = stopwords.words('english') output = [w for w in processed_docs if not w in stop_words] print("n"+str(output[0]))

    I have used stop word function present in the NLTK library. The first list contains the list of stop words considered by the system. The second list contains the list of words after the stop words have been removed.

    We will be left with only the keywords once the stop words are removed. This step is important for any NLP processing.

    Stemming

    Stemming means cutting out the other parts of a word and keeping only the stem (i.e. the important part of the word). In English, we add prefixes and suffixes to a word to form different words/tense forms of the same word.

    For example, the root word stem can take the form of stemming or stems. The stemming process will remove the suffix to give out the word – stem. I have performed both the stemming as well as the lemmatization process explained in the next step together. The code snippet for both is attached together in the next step. I have attached an example for stemming in the code below. You can notice that the word “queens” has been stemmed to “queen“.

    from chúng tôi import PorterStemmer from nltk.tokenize import word_tokenize ps = PorterStemmer() a = doc_sample.split(' ') for w in a: print(w, " : ", ps.stem(w))

    Another example is the word ecosystem. The root word for this is “eco” while the derived word is “ecosystem“. You do not need to be a grammar expert to perform stemming. Python has libraries that support the stemming process.

    Lemmatization

    Lemmatization is similar to stemming but is different in a complex way. Stemming simply cuts out the prefix or the suffix without thinking whether the remaining root word makes sense or not. Lemmatization on the other hand looks at the stemmed word to check whether it makes sense or not.

    For example, the word “care” when stemmed will give out “car” but when lemmatized will give out “care”. The root word care is called a lemma.

    So why is lemmatization very important?

    Lemmatization helps in the disambiguation of words. It brings out the actual meaning of the word. So if you have multiple words which share a similar meaning, lemmatization can help sort this out. Hence, this is a very important step for your NLP process.

    def lemmatize_stemming(text): snow_stemmer = SnowballStemmer(language='english') return snow_stemmer.stem(WordNetLemmatizer().lemmatize(text, pos='v')) def preprocess(text): result = [] for token in gensim.utils.simple_preprocess(text): result.append(lemmatize_stemming(token)) return result doc_sample = documents[documents['index'] == 1018].values[0][0] print('original document: ') words = [] for word in doc_sample.split(' '): words.append(word) print(words) print('nn tokenized and lemmatized document: ') print(preprocess(doc_sample))

    You can see the steps used to stem and lemmatize the same news article document. Here, I have used a snowball stemmer for this process.

    Modelling 

    Modeling your text is very important if you want to find out the core idea of the text. I the case of supervised machine learning, we use logistic regression or linear regression, etc to model the data. In those cases, we have the output variable which we use to train the model. In this case, since we do not have the output variable, we rely on unsupervised techniques.

    There are a lot of good algorithms to help model the text data. Two of the most commonly used are the SVD (Singular Value decomposition) and LDA (latent Dirichlet allocation). These are widely used across the industry and are pretty simple to understand and implement.

    LDA is a probabilities algorithm that focuses on iteratively assigning the probability of a word belonging to a topic. I have used LDA here to identify the possible topics for an article.

    lda_model = gensim.models.LdaMulticore(bow_corpus, num_topics=10, id2word=dictionary, passes=2, workers=2)

    Here, you can see the probabilities being listed out for each article. Each keyword has a value that states the likeliness of the word being the keyword.

    Conclusion

    What I have listed out are some of the key steps in NLP. NLP is a dimension onto itself. To fully understand the magnitude of it, we need to first understand how deep any language can be. Since, NLP focuses on text data based on language, irony, sarcasm, comedy, trauma, horror, and many more such things need to be considered.

    On a parting note, I wish to bring to your attention that the possibilities using NLP are limitless. The industry has realized the value of the text data of late and has started exploring more on this. Even the automated chatbots which pass the turning test have some amount of NLP embedded in them.

    About the Author

    Hi there! This is Aishwarya Murali, currently working in the analytics division of Karnataka Bank’s – Digital Centre of Excellence in Bangalore. Some of my interesting projects include ML-based scorecards for loan journey automation, customer segmentation, and improving the market share via selective profiling of customers using some machine learning analytics.

    I have a master’s in computer applications and have done certification in Business Analytics from IIM-K. Currently, I am working on R&D innovations at my workplace.

    You can connect with me at

    You can also mail me at

    [email protected]

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