Abhishek mamidi - DS

I always wanted to share my detailed Data Science journey. So, I have divided the whole journey from BTech first year to final year into 3 parts. I will share everything, without leaving a single detail, starting from my projects, internships to getting a job. You can follow the path that I have followed if you like my journey or create your own path. In 2015, I got a seat in Electronics and Communication Engineering (ECE), IIIT Sri City through IIT JEE Mains. Because of my rank in JEE Mains, I couldn’t get into the Computer Science department. I wanted to shift to Computer Science after my first year, but couldn’t due to some reasons. In our college, we have only two branches, CSE and ECE. For the first three semesters, the syllabus was the same for both the departments except for a few courses. This helped me to explore Computer Science. In the first 3 semesters, I took Computer Programming, Data Structures, Algorithms, Computer Organization, Operation Systems courses, wh

Exploratory Data Analysis is the foremost step while solving a Data Science problem. EDA helps us to solve 70% of the problem. We should understand the importance of exploring the data. In general, Data Scientists spend most of their time exploring and preprocessing the data. EDA is the key to building high-performance models. In this article, I will tell you the importance of EDA and preprocessing steps you can do before you dive into modeling. I have divided the article into two parts: Exploratory Data Analysis Data Preprocessing Steps Exploratory Data Analysis Exploratory Data Analysis(EDA) is an art. It’s all about understanding and extracting insights from the data. When you solve a problem using Data Science, it is very important to have domain knowledge. This helps us to get the insights better according to the business problem. We can find the magic features from the data, which boost the performance. We can do the following with EDA. Get comfortable with

Interviews are very stressful. We should prepare for the worse. So, we have to plan accordingly in order to crack them. In this blog, you will get to know the type of questions that will be asked during the interview. It also depends on the experience level and the company too. This blog is mainly focused on entry-level Data Science related jobs. If you haven’t read my previous blog-posts, I highly recommend you to go through them: Skills required to become a Data Scientist How to apply for a Data Science job? First of all, you must be thorough with your resume, mainly your Internship experience and academic projects. You will have at least one project discussion round. Take mock interviews and improve your technical and presentation skills, which will surely help in the interviews. Based on my experience, I have curated the topmost 35 frequently asked Data Science questions during the interviews. Explain the Naive Bayes classifier? In case of Regression, how do y

Job search is one of the painful tasks. We have to invest a lot of time to get placed in one of the best companies, we were dreaming for. The demand for Data Scientists is increasing over the years, and we have to stand out of the crowd to get a job. In this post, I will guide you on “How to apply for a Data Science job?”. I have divided the blog post into the following: What are the skills required for a Data Science job? How to build a good Data Science profile/resume? What are the different ways of applying for a Data Science job? What are the skills required for a Data Science job? I have created a blog-post on “Skills required to become a Data Scientist”, last week. I would suggest going through the previous blog before you go to the next section. How to build a good Data Science profile/resume? After acquiring the necessary skills, it is required to maintain a good Data Science profile. Your presence on the social network makes a difference too. Some tips