Data Science Tips for Beginners!

  Q1. You are given a train data set having 1000 columns and 1 million rows. The data set is based on a classification problem. Your manager has asked you to reduce the dimension of this data so that model computation time can be reduced. Your machine has memory constraints. What would you do? (You are free to make practical assumptions.) Answer: Processing a high dimensional data on a limited memory machine is a strenuous task, your interviewer would be fully aware of that. Following are the methods you can use to tackle such situation: Since we have lower RAM, we should close all other applications in our machine, including the web browser, so that most of the memory can be put to use. We can randomly sample the data set. This means, we can create a smaller data set, let’s say, having 1000 variables and 300000 rows and do the computations. To reduce dimensionality, we can separate the numerical and categorical variables and remove the correlated variables. For numerical variable...

Here are the 10 MOST IMPORTANT tips for making you a Compelling value proposition & helps create an impact. 1. From the PORTFOLIO OF PROJECTS which is actually your LIVING RESUME, choose ONE project that you are SURE about to talk & your story SHOULD cover the following at a minimum with Demonstrable evidence

Interviewer: You have only 10 minutes to impress me. Me: Okay sir. Can I do anything in this time to impress you? Interviewer: Yes, but don’t cross your limits. Me: Sure, sir. Let’s

  Statistics & Probability Intro-to-Descriptive-Statistics How To Ace Data Science Interviews: Statistics

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This Python Cheat is from the Book Python Crash Course which aims to remind you of syntax rules and grasp all the important concepts in Python programming as a beginner. You will also

This Python Cheat Sheet presents the Python basics that you need to do data science and will guide you through variables and data types, Strings, Lists, to eventually land at the fundamental package for scientific

Here is what we're finding mistakes in thousands of cvs: 1. Summary: CV should have a short summary of your experience, skills, achievements, so that a recruiter need not read the full cv. 3-4 Bullet points at the top of the CV can summarize it. 2. Length: CV should

It is so good to be interested about Data Science and Machine Learning. Many students think that Data Science is a non technical subject and people with zero coding knowledge, no logical thinking, no creativity can pursue data science courses and can become a Data Scientist. To all those students, looking for building a good portfolio for Data Science, here are some tips to follow: 1. Certifications and courses are not going to take you

550+ Computer Science and Programming Books List. A Collection of Test Problems for Constrained Global Optimization Algorithms - Floudas and Pardalos.pdf A Distributed Pi-Calculus - Hennessy.pdf A First Course in Database Systems 3e - Ullman and Widom.pdf A Guide to MATLAB for Beginners and Experienced Users - Hunt, Lipsman, and Rosenberg.pdf A Practical Guide to Boundary Element Methods with the Software Library BEMLIB - Pozrikidis.pdf A Programmer's Introduction to C# - Gunnerson.pdf A Smarter Way to Learn JavaScript - Meyers.pdf A Theory of

Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data ➼ The Most Complete List of Best AI Cheat Sheets. ➼ Neural Networks Graphs Cheat Sheet ➼ Machine Learning Overview MACHINE LEARNING IN EMOJI ➼ SUPERVISED

Have you ever been confused between paying for a course on coursera, udemy for certificate or downloading it from internet for free. "One good Project is always superior than 5 certificates". With zero knowledge of C and a keen interest to learn it, I looked upon the internet for the courses offered by some websites which I found paid. In reality, many students

14 Quick Tips for Finding a New Job: 1. Get clear on what you want 2. Research your target companies 3. Tailor your resume to each job 4. Create your online career brand 5. Get organized

I have summarized in this text best tips for data scientists to progress along their career. Whether you’re just starting or you want to go from junior to mid or mid to senior, there’s something new here for you. It's good to know about regression, Clustering,classification ensemble models however theses algorithms are now being taken care by Auto ML packages. Now, the hiring organisations are

Top 50 Machine Learning Interview Questions and Answers. 1) What is Machine learning? Ans - Machine learning is a branch of computer science which deals with system programming in order to automatically learn and improve with experience. For example: Robots are programmed so that they can perform the task based on data they gather from sensors. It automatically learns programs from data. 2) Mention the difference between Data Mining and Machine learning? Ans - Machine learning relates with

📇Top Machine Learning Algorithms📉 Naïve Bayes Classifier Algorithm K Means Clustering Algorithm Support Vector Machine Algorithm Apriori Algorithm Linear Regression Logistic Regression Artificial Neural Network Random Forests Decision

Break into Data Science Become A Data Science Expert Build up your ability to ingest, transform, visualize and model datasets. Whether you’re new to data science, or just need to brush up and expand your knowledge. Learn mathematics, statistics, SQL, Python, data cleaning and visualization, and machine and

Solved a DS/Algo question & forget it after a week? Don't worry I have a SECRET tip for you. "update your `mind cache` with Fibonacci Sequence Interval, starting from index=2" Explanation: 0. Suppose you solved a problem on

NumPy NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and

An outlier is an observation that is unlike the other observations. It is  rare, or distinct, or does not fit  in some way. Outliers can have many causes, such as: