Tensorflow: The Confusing Parts (1)

The tutorial for beginners by Jacob, Google AI Resident. This can be nice intro for those, who wanted to get familiar with #TF

This is thorough introduction to the concepts underlying Tensorflow’s API; such as nodes, graphs and sessions.

https://jacobbuckman.com/post/tensorflow-the-confusing-parts-1/?utm_source=telegram&utm_medium=opendatascience

#tensorflow #tutorial #novice #beginner

A visual introduction to machine learning.

It is an interactive website, which would be really useful to the beginners, as a perfect visual explanation of how decision trees work. It shows how one can go from statistical parametric evaluation to decision tree building.

Link: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/?utm_source=telegram&utm_medium=opendatascience

#decisiontrees #beginner #novice #firststep #howitworks

Model Tuning and the Bias-Variance Tradeoff
(part II of Visual Introduction to Machine Learning by r2d3)

Bias-Variance tradeoff happens because you have to find optimal balance between model being too simple and too complex. Too complex models tend to overfit — to become to adapted to the training data, so the results on the testing (new, unknown to model) data become less accurate. The article explains with the example from previous part how this actually works.

http://www.r2d3.us/visual-intro-to-machine-learning-part-2/?utm_source=telegram&utm_medium=opendatascience

#decisiontrees #beginner #novice #firststep #howitworks

Nice hot start on data streaming with #Spark

https://towardsdatascience.com/learn-how-to-code-and-deploy-machine-learning-models-on-structured-streaming-564749840516

#scala #bigdata #streaming #kafka #tutorial #novice #beginner

Pitfalls of Batch Norm in TensorFlow and Sanity Checks for Training Networks

Some more practical advices on #tensorflow training with source code and reference links to look up.

https://medium.com/@theshank/pitfalls-of-batch-norm-in-tensorflow-and-sanity-checks-for-training-networks-e86c207548c8

#beginner #novice #dl #tutorial

Adversarial attack — type of input or a mask applied to the input of the machine learning model to make it wrong. It is a way to cheat with the output, to ‘fool’ the algorithm.

«Attacking Machine Learning with Adversarial Examples» at Open AI blog covers the basics and provides some examples.

Open AI blog article: https://blog.openai.com/adversarial-example-research/

#adversarialattack #openai #novice #beginner

Most common pitfalls, you can encounter when training neural network.

http://telegra.ph/Most-common-neural-network-mistakes-07-01

#beginner #novice #dl #tutorial

How to Create Animated Graphs in Python

Short tutorial on how to create animated graphs, which also works in #jupyter notebooks.

Link: https://towardsdatascience.com/how-to-create-animated-graphs-in-python-bb619cc2dec1
Youtube link with #visualization: https://youtu.be/7xrvuSDLHiY|

#novice #beginner

Data Types From A Machine Learning Perspective With Examples

This is a really #beginner level article about how different data types can be categorized.

Link: https://towardsdatascience.com/scala-for-data-science-engineering-part-1-6a0a5738d7b0

A set of best where-to-start-with-python resources.

This is the collection of beginners resources from a tweet by fast.ai cofounder, covering any resource which helped people to learn python from scratch.

https://telegra.ph/A-collection-of-where-to-start-python-resources-11-05

#beginner #novice #CS #python #tutorial