Tag: Data Analysis

Interview with a Kaggle Master & More
1. Exclusive Interview with 2x Kaggle Master Gilles Vandewiele! “I think one of the nice things about the data science field is that it is so multidisciplinary and that anyone who aspires to become a data scientist can do so.” – Gilles Vandewiele Golden words! As a beginner in data science, this quote gives me […]

Top 5 Data Science & Analytics Online Courses
There is an increasing demand for data science experts in different industries today. In this datadriven economy, it is only natural for data to be a valuable asset in the efficient working of an organization. However, finding a job in this sector requires you to have a set of certain skills and some solid educational […]

Natural Language Processing Usecases with Python
1. Master Natural Language Processing in 2022 with Best Resources As already mentioned earlier, Deep Learning is a subdomain of machine learning. It is far more generalized as it comes up with generalized predictions compared to traditional machine learning due to the introduction of Artificial Neural Networks or ANN. Practicing NLP with Deep Learning is an […]

10 DATA SCIENCE SPECIALIZATIONS
It is absolutely normal that we come across a growing number of specializations within the field of Data Science. This will help you in understanding in which area you want to work eventually. 1. DATA MINING Data mining, also known as knowledge discovery in data (KDD) is the process of finding and extracting anomalies and discovering patterns in large data sets to predict outcomes. In simple terms, the main aim of data mining is to extract information with intelligent methods and transform the information into a comprehensible structure. 2. DATA VISUALIZATION It provides a convenient way of understanding trends, outliers, and patterns in data. Data visualization is the domain that deals with the graphic representation of data through visual elements like charts, graphs, maps, and other visualization tools. 3. DATA PROCESSING We can also call it manipulation of data by computers inclusive of output formatting or transformation. Data processing is when you collect data and transform data into useful information. 4. DATA CONSULTANCY It also involves educating companies or clients about various aspects of data technology. They provide a wide range of methods that optimizes business intelligence by leveraging existing data. 5. MARKET DATA ANALYTICS Through it, we can identify the strengths, weaknesses, opportunities, and potential threats of a company. It looks into the depths of consumer segments, buying patterns, competition, and the economic environment. 6. CYBERSECURITYRTY DATA ANALYSIS These experts produce intelligence to improve the security and privacy of data of an organization from external and internal threats. Cybersecurity uses data science to protect software and devices from cyberattacks. 7. DATA ARCHITECTURE Data architecture refers to how an organization collects, store, transform, distribute and use data. These days it is important for organizations to have centralized data architecture in accordance with industry standards. 8. DATA ENGINEERING Their primary job is to design, manage and optimize the flow of data with databases throughout the organization. It is the practice of designing and building data systems for collecting, storing, and analyzing data at scale. 9. BUSINESS INTELLIGENCE AND DATA ANALYTICS It describes the strategies, technologies, and tools companies further use to obtain important business information. Data analytics ad data analytics are their subsets that provide data management solutions to understand contemporary data and gain relevant insights. 10. COGNITIVE MACHINE LEARNING Cognitive computing systems work with humans and provide them with advice in making informed decisions. It intends to use the best algorithm and come up with an accurate action/result.

Logistic Regression in Machine Learning (from Scratch !!)
Introduction In this blog post, I would like to continue my series on “building from scratch.” I will discuss a linear classifier called Logistic Regression. This blog post covers the following topics, Basics of a classifier Decision Boundaries Maximum Likelihood Principle Logistic Regression Equation Logistic Regression Cost Function Gradient Descent Algorithm After the discussion of […]

Data Science & Its Applications
WHAT IS DATA SCIENCE? There are high chances that you have come across the term ‘data science.’ It is highlysupported by the fact that a career in data science is deemed to be one of the mostsoughtafter and promising careers of the times. Given the enormous amounts of dataproduced on a daily basis, it becomes […]

IPL Score Prediction Using Machine Learning
Introduction With the IPL season coming up (for those who are not familiar with IPL, it’s the EUROPA League or the NBA of Cricket in India and all the cricketing nations) I wanted to share the use case of Data Science in cricket. Data Science and Analytics are being used in Sports extensively. You can […]

Probability Distributions that every Data Scientist must know
Introduction Probability of an event tells us how likely is that, the event will occur. The applications of probability begin with the numbers p0, p1, p2… that give the probability of each possible outcome. There are dozens of famous and useful possibilities for p. I will discuss four of them in this post. Before going […]

Data Science Starters
So, this post is for someone who wants to learn Data Science but is not able to find where to start from. In this post, I will share some crucial resources (free) that would help you get started with your Data Science journey, Programming So, to get started with Data Science you must be fluent […]

Heteroscedasticity
In this post, I want to talk about Heteroscedasticity. I can understand, some of you might have a hard time pronouncing it (atleast I did). Anyway, we are more interested in its meaning and it’s application rather than its pronunciation. So, Heteroscedasticity means the variability of a random disturbance is different across a vector. Now, […]