What I Wish Everyone Knew About K Means : Unsupervised Learning

K Means is one of the simplest unsupervised learning methods. Now, question comes what is Unsupervised learning? Lets have quick overview.

Unsupervised learning is the method where we train the model provided training data has no labels / dependent features.

Few keywords and their description before we understand K means:

Features : Training data has different columns and these are considered as features. They are also termed as independent variables.

Labels : Data used for trainings has labels or output variables/features. These are also called dependent variables. They are called dependent as their outcome depends upon the independent variables.


Developing Model and Tuning Steps For NLP

NLP stands for natural language processing and it is one of the buzzword in real world. Everybody wants to learn and expertise in this area. To start, NLP is directly correlated to processing text and we all know today’s world is full of text flowing from everywhere. This much data and processing it becomes very interesting. It brings lots of use cases, innovation and ideas to apply machine learning.

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With the above discussion, we can understand how important and vast is text processing. It becomes difficult when it is very easy to implement and everybody can write simple lines of…

Master visualization to explore data in first go

Python is one of the new generation languages. It has libraries to visualize your data, explore and get some insights out of the same. Matplotlib is one of the libraries which is used most common in exploring the data. Every data analysis requires to visualize the data for different purpose like finding outliers, density, sparcity, trends and more importantly normalization of data.

Let us explore matplotlib and then we can see what are the other libraries for visualization.

Plotting the data to visualize and extracting first level meaning from the data is…

Learn this Library to Excel as Data Scientist

Pytorch is very known open source library which can be used for building neural network and natural language processing solutions. There are many advantages of this library over other libraries but the most visible one is change in processing internally and finally, achieving faster execution in evaluations performed across vectors. In other words, it emphasizes on faster processing of huge numerics in the best possible manner.

Pytorch : open source library + NLP + Faster processing / execution

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Another Library with advanced features and flexibility

In comparison to tensorflow, it has all the replica libraries which can perform at similar capacity with faster execution. …

Text to Vector space, A Step Closer to Analysis and Must for Data Science Projects

Natural language processing (NLP) has capability to handle text and provide meanings to that based on the problem statement. First and foremost question arises, how machine can handle text. So, NLP is not different and it also converts text into vectors of numbers to have meaning from the words. Once everything is in the form of vector, it is easy to compare and evaluate the same. It makes it understandable that NLP also converts the data into vector and ML model requires data in numeric to train the model. …

Data Processing using NLTK in Python and Visualizing the Same using WordCloud

NLP stands for Natural Language Processing. As name suggests, it deals with text as input and has the ability to extract meaning out of given text like human. Two decades ago, it could be a challenge to get the data and scarcity of data to train the model did not bring success to NLP. Now, world has moved so fast that getting data is very easy specially in text format, the challenge is to handle huge amount of data and interpret the data in the most appropriate manner to Problem Statement. There is huge amount of data travelling on daily…

Another Learnings for any Data Scientist

Time series is one of the examples which can suit to any transactional related problem statement. So, time series analysis is buzzword, must to learn and challenge to understand to resolve. Concluding time series problem has been a major task to be achieved as ML engineer or Data Scientist. Famous use cases are cash flow analysis & forecasting, stock market, weather and electricity demand forecasting etc. In simple words, wherever we can find seasonal or random variations we can definitely take it as time series analysis to come to conclusion. Here, I will go through four techniques to handle time…

Fuzzy Logic with Genetic Algorithm to Make Profit in Trading

Algotrading is one of the buzzwords and it is well understood that machine is trading on your behalf to give you profit. I would like to term it as quantitative analysis system which will read the past time series data for trades/currency and based on that, make a decision to buy/sell/hold. Our use case is that where we have some initial amount, previous price index and today’s price index. And, our goal is to let algorithm do the trading and gives us the profit at the end of 15 days.

5 Types of Analytics and Their Meaning With Usage

Analysis and steps involved in analysis are very important to reach to the right conclusion. It will help to derive meaning out of raw data which most of the world is striving for. This brings us to the discussion of different types of analysis and their respective importance in data analytics. To be frank, knowing them will give depth of understanding to utilize the same in actual environment and have edge over others.

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Different Analytics Types

Descriptive Analytics

This is the first stage in the business analytics in the modern day. This stage will give quite a good analysis about the raw data. …

Proper and Designed Process to Succeed in Your Learning : Must Plan to Learn

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Learning also requires proper planning

There is introduction of new technologies and programming languages happening in a very rapid rate. Everybody wants to add new leaf into their programming vocabulary. And, once you start learning new programming languages, you will find many advices and lots of things. You end up wasting your lots of time in starting your journey. You won’t understand whom to rely or not. Learning a new language has become an art and if we do in organised manner, learning could be achieved more faster than actual. In my view and understanding with my learning process over the years, I have come…

Laxman Singh

Machine Learning Engineer | Data Science | MTECH NUS, Singapore

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