Data science column Skills that every ML, AI engineer must have Before coming to the skillsets required to become a successful ML/AI engineer & derive a prospering career in this field; it is first important to understand the key requirements & nitty-gritties involved
Data science column Why statistics is so important in data science? The onset and generation of huge volumes of data being collected day in and day out has made it almost impossible for businesses to perform a qualitative analysis of performance & happenings. Now
Data science column Data Science projects for beginners Data Science, or for that matter concept or technology in the space of Analytics, is best learnt via projects and practical implementation rather than going in depth in theories & frameworks. While it
Data science column Big Data Technology Stack used by top companies Many users from the developer community as well as other proponents of Big Data are of the view that Big Data technology stack is congruent to the Hadoop technology stack (as Hadoop as
Data science column Impact of big data in decision making Big Data & its implications on business has often been compared to an iceberg which has more than 90% of the mass submerged under water (and only 10% visible). Hence, designing information &
Data science column The important area of machine learning using Python - Supervised Learning Supervised & unsupervised learning systems are two major categories of teaching a machine learning system to take self-governed decisions. Now, before dwelling deep into the nitty-gritty of supervised learning; it is important to
Data science column Why is Python popular in Machine Language? There are a multitude of languages and programming frameworks which supports or enables machine language applications; however, Python is considered to be the forerunner in machine language both from a utility perspective as
Data science column Difference between Artificial Intelligence & Machine Learning Artificial Intelligence & Machine Learning, at times, are used interchangeably by users & developers. Although there is a fair amount of correlation between the two; still the terms & its concepts are not
Data science column Deep Learning - Dive into the World of Machine Learning! Deep Learning is a finer and sophisticated branch of machine learning which is largely based on artificial neural networks. Also known as hierarchical learning, deep learning algorithms are closest to the way human
Data science column Most important Python Libraries for Data Science According to the 2019 StackOverflow Developer Survey. Python is the fastest-growing major programming language today second only to Javascript. It has become the most loved and the most wanted language in 2019 and
Data science column What is Jupyter Notebook? and Why it is the Best Tool for Data Science Data is of no use if you can’t turn it into insights if you can’t analyze it, if you can’t explore or share it. Jupyter, an acronym meaning Julia, Python,
Full Stack Development Column Front End v/s Back End v/s Full Stack Which one should you learn? Today, the internet is nothing without websites. Truckloads of information presented to you in one click, in a suave looking manner with impressive visuals and a logical format. Who do you think, makes
Data science column Role of Machine Learning in Social Media Services As social media has become one of the biggest platforms for business expansion and branding, organizations are making use of machine learning to enhance user experience and promoting their brand. Everyone around the
Data science column Who Is A Data Scientist and What Are The Various Fields In Data Science? Data scientists thrive on data. They are professionals who are responsible for collecting, analysing and interpreting huge amounts of data, to gather solutions to all business problems and challenges. The data could be
Data science column Roles Available In The Field Of Data Science Data is revolutionizing the way we interact with various systems, every day. Be it your Google Home, Siri, Alexa or even you browsing your Instagram, it’s all a by-product of data analysis.
Data science column Difference between Data Analyst, Data Scientist & Business Analyst You might be familiar with the terms Data Analyst, Data Scientist and Business Analyst. These terms have become very popular as these jobs are highly desirable and well paid in today’s date.
Resume column How to write a rejection follow-up letter So you’ve gone through multiple rounds of interviews, sent your follow up thank-you emails and you’re patiently waiting—and you see this email which says you’re not selected. Yes, that
Talent Corner In conversation with Talent Manager at Bridge I2I on essential skills in Analytics Bridge I2I provides AI-powered analytics solutions to solve complex business problems and deliver digital transformation outcomes to their clients. The AI accelerators simplify and democratize consumption of insights and recommend the right business
Data science column Why do companies hire big data analysts? We are living in a world which is dominated by data. Data is being generated from multiple different sources in a very large quantity and at a very high speed, every day. Every
Data science column Essential Machine Learning Algorithms Machine learning algorithms help data scientists to work on complex problems and solve them. If you are an aspiring Data Scientist, you need to have good knowledge of these algorithms too. Let’s
Data science column What is big data? It’s types and characteristics Big Data is a widely discussed topic today and with good reason too! This technology has brought some amazing inventions and innovations to our world which has changed our lives for the better.
Data science column Difference between Machine Learning,AI, Data Science & Deep Learning Machine Learning, AI, Deep Learning and Data Science are very closely related areas of study and most people often confuse them to be the same. However, there is a significant difference between the
Data science column Why is everyone talking about AI & Machine Learning It seems like the entire world is obsessed with AI and Machine Learning and the market is buzzing with talks on this subject alone. However, to the unaware, it may seem like a
Data science column What is machine learning? In the past few decades, there has been a volcanic eruption of data. What’s the use of so much data if it’s not analysed and no insights are derived from it?
