There are so many parameters and hyperparameters (all referred to as parameters hereon) to tune with a neural network, so where to start?
In Professor Andrew Ng’s Deep Learning Specialization courses, he gives the following guideline:
These are great tips. But, to make them part of our skills, we need intuition :) To achieve that, I built a customizable neural network class in Python and conducted a series of experiments to verify the ideas. Let’s see!
TensorFlow is the dominating Deep Learning framework for Data Scientists and Jupyter Notebook is the go-to tool for Data Scientists. What if you can use TensorFlow from anywhere without the hassle of setting up the environment? Better yet, what if you can use GPU to train your Deep Learning models for free?
Google Colaboratory (Colab)is the answer! It is a very exciting technology that allows Data Scientists to focus on building Machine Learning models instead of the logistics!
In this article, we’ll not only walk through the basics of using Colab, but also help you get started with TensorFlow with…
It is often said that the majority of a Data Scientist’s work is not the actual analysis and modeling, but rather the data wrangling and cleaning part. As a result, full-cycle data science projects that involve these stages will be more valuable since they prove the author’s abilities to work independently with real data, as opposed to a given cleaned dataset.
Fully understanding the value of an end-to-end data science project, I always wanted to build one but not able to, until now :)
I have recently finished my Ideal Profiles project. Since it’s a major project that involves many…
(This is part 2 of my Data Science Careers project. You can find the first part here.)
If you are a Data Science job seeker, you must be wondering all the time what skills to put on your resume to get calls; if you are looking to get into the field, you may have scratched your head many times wanting to know which technologies to learn to be an attractive candidate.
Read on, I have the answer for you.
First, we look at the skill requirements for different job titles. (charts follow)
There once was a debate of whether Python…
If you are thinking of starting a career in data science, you probably agree that things are a bit confusing in this field! What is a Data Scientist anyway? What’s the difference between a Data Analyst and a Data Scientist? What does a Machine Learning Engineer do? What about a Data Engineer, Business Intelligence (BI) Engineer, and Machine Learning (ML) Researcher…?
In this post, we’ll take inventory of different roles in data science, explain what they are and the differences between them. We’ll also establish an “ideal profile” for each one. This is important for career satisfaction and job search…
Over the last several years, I’ve subscribed to many data science newsletters to keep myself up-to-date with the latest developments in the field and to discover new learning resources. I have learned a ton from these. In particular, I found the following curated list most useful, and I believe it’s also the most comprehensive list of data science newsletters, on the Internet :) So let’s see!
After spending numerous evenings and weekends learning and coding for more than a year, you finally did it! You’ve now completed your data science program, earned your shiny certificate…now what? Chances are you were looking to get a job in data when you signed up for the course. So let’s face this, it is time to get a job! The only thing that’s standing between you and success is that first data science job offer. But how?
Look no further, follow these proven steps that have helped many data science enthusiasts like you secure job offers.
Without a direction, any…