If you need to deal with unstructured data (perceptual tasks): Keras or PyTorch.
The two main machine learning techniques used in the industry today:
1. Gradient Boosted Trees
2. Deep Learning
Focus your time learning Scikit-Learn, XGBoost, and a Deep Learning library like Keras or PyTorch and you'll get the most for your time.
If you need to deal with unstructured data (perceptual tasks): Keras or PyTorch.
More from Santiago
Free machine learning education.
Many top universities are making their Machine Learning and Deep Learning programs publicly available. All of this information is now online and free for everyone!
Here are 6 of these programs. Pick one and get started!
↓
Introduction to Deep Learning
MIT Course 6.S191
Alexander Amini and Ava Soleimany
Introductory course on deep learning methods and practical experience using TensorFlow. Covers applications to computer vision, natural language processing, and more.
https://t.co/Uxx97WPCfR
Deep Learning
NYU DS-GA 1008
Yann LeCun and Alfredo Canziani
This course covers the latest techniques in deep learning and representation learning with applications to computer vision, natural language understanding, and speech recognition.
https://t.co/cKzpDOBVl1
Designing, Visualizing, and Understanding Deep Neural Networks
UC Berkeley CS L182
John Canny
A theoretical course focusing on design principles and best practices to design deep neural networks.
https://t.co/1TFUAIrAKb
Applied Machine Learning
Cornell Tech CS 5787
Volodymyr Kuleshov
A machine learning introductory course that starts from the very basics, covering all of the most important machine learning algorithms and how to apply them in practice.
https://t.co/hD5no8Pdfa
Many top universities are making their Machine Learning and Deep Learning programs publicly available. All of this information is now online and free for everyone!
Here are 6 of these programs. Pick one and get started!
↓

Introduction to Deep Learning
MIT Course 6.S191
Alexander Amini and Ava Soleimany
Introductory course on deep learning methods and practical experience using TensorFlow. Covers applications to computer vision, natural language processing, and more.
https://t.co/Uxx97WPCfR

Deep Learning
NYU DS-GA 1008
Yann LeCun and Alfredo Canziani
This course covers the latest techniques in deep learning and representation learning with applications to computer vision, natural language understanding, and speech recognition.
https://t.co/cKzpDOBVl1

Designing, Visualizing, and Understanding Deep Neural Networks
UC Berkeley CS L182
John Canny
A theoretical course focusing on design principles and best practices to design deep neural networks.
https://t.co/1TFUAIrAKb

Applied Machine Learning
Cornell Tech CS 5787
Volodymyr Kuleshov
A machine learning introductory course that starts from the very basics, covering all of the most important machine learning algorithms and how to apply them in practice.
https://t.co/hD5no8Pdfa

Here is a simple example of a machine learning model.
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.
The goal of this model is to learn to multiply one-digit
I put it together a long time ago, and it was very helpful! I sliced it apart a thousand times until things started to make sense.
It's TensorFlow and Keras.
If you are starting out, this may be a good puzzle to solve.

The goal of this model is to learn to multiply one-digit
It is a good example of coding, what is the model?
— Freddy Rojas Cama (@freddyrojascama) February 1, 2021