As you might know, I regularly write on Medium covering topics such as Artificial Intelligence, Machine Learning, Deep Learning, Data Science, Data Visualization, TensorFlow, and other programming topics. Since the volume of my content reached a certain level, it got harder to see what I wrote about. So, I put together this guide to help you navigate around my content with ease.
If you are reading this article, I am sure that we share similar interests and are/will be in similar industries. So let’s connect via Linkedin! Please do not hesitate to send a contact request! Orhan G. Yalçın - Linkedin
Before diving into this article, I just want to let you know that if you are into deep learning, I believe you should also check my other articles such as:
1 — Image Noise Reduction in 10 Minutes with Deep Convolutional Autoencoders where we learned to build autoencoders for image denoising;
2 — Predict Tomorrow’s Bitcoin (BTC) Price with Recurrent Neural Networks where we use an RNN to predict BTC prices and since it uses an API, the results always remain up-to-date. …
In Part-I of this tutorial, we developed a small python program with less than 20 lines that allowed us to enter the first Kaggle competition.
However, this model did not perform very well since we did not make good data exploration and preparation to understand the data and structure the model better. In Part-II of the tutorial, we will explore the dataset using Seaborn and Matplotlib. Besides, new concepts will be introduced and applied for a better performing model. Finally, we will increase our ranking in the second submission.