Monday, 2 December 2019

Most Influential Articles 2019 At Towards Data Science

Amazing content from Towards Data Science community 2019:

Turn Python Scripts into Beautiful ML Tools

Introducing Streamlit, an app framework built for ML engineers

Everything a Data Scientist Should Know About Data Management*

(*But Was Afraid to Ask)

Introduction to Decision Intelligence

A new discipline for leadership in the AI era

Becoming a Level 3.0 Data Scientist

Want to be a Junior, Senior, or Principal Data Scientists? Find out what you need to do to navigate the Data Science Career Game.

Extreme Rare Event Classification using Autoencoders in Keras

In this post, we will learn how to implement an autoencoder for building a rare-event classifier. We will use a real-world rare event dataset

The Next Level of Data Visualization in Python

How to make great-looking, fully-interactive plots with a single line of Python

Beginner’s Guide to Machine Learning with Python

Machine Learning, a prominent topic in Artificial Intelligence domain, has been in the spotlight for quite some time now.

12 Things I Learned During My First Year as a Machine Learning Engineer

Being your own biggest sceptic, the value in trying things which might not work and why communication problems are harder than technical problems.

Using the latest advancements in deep learning to predict stock price movements

In this notebook I will create a complete process for predicting stock price movements.

Understanding Random Forest

How the Algorithm Works and Why it Is So Effective

Data Science is Boring

How I cope with the boring days of deploying Machine Learning

10 Simple hacks to speed up your Data Analysis in Python

Tips and Tricks, especially in the programming world, can be very useful.

The Actual Difference Between Statistics and Machine Learning

No, they are not the same. If machine learning is just glorified statistics, then architecture is just glorified sand-castle construction.

A beginner’s guide to Linear Regression in Python with Scikit-Learn

There are two types of supervised machine learning algorithms: Regression and classification.

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