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

Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

List mostly for beginners.

Link: https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html

#novice #beginner #ipython #jupyter

Deep learning for NLP crash course at ABBYY.

Github repo with scheduled plan for learning #DL #NLP online.

Link: https://github.com/DanAnastasyev/DeepNLP-Course

#educational #tutorial #course #beginner #novice #entrylevel

Upcoming series of #ML lectures from Columbia Universite will be published on youtube.

If you are looking #wheretostart, this is one of the great places.

YouTuve Playlist: https://www.youtube.com/playlist?list=PL_pVmAaAnxIQGzQS2oI3OWEPT-dpmwTfA
Syllabus: https://www.cs.columbia.edu/~amueller/comsw4995s19/schedule/

#beginner #novice #entrylevel

Free online ODS.AI course on ML

Another great free course will start on February 11. Taught through #Kaggle notebooks and competitions.

Link: https://www.kaggle.com/general/77771

#entrylevel #novice #beginner

Probabilistic foundations of econometrica: part 1

Great intro into #statistics basics.

Link: https://freakonometrics.hypotheses.org/57649

#beginner #novice #entrylevel

Really short and brief, yet useful #tutorial on #PyTorch #transferlearning

Transfer learning is a concept of using network trained for a certain task for another one.

Link: https://medium.com/@iamHarin17/transfer-learning-in-pytorch-f7736598b1ed

#DL #novice #entrylevel #beginner

Time series basics

Time series — data, with points having timestamps. Some might think that #timeseries are mostly used in algorithmic trading, but they often used in malware detection, network data analysis or any other field, dealing with some flow of time-labeled data. These two resources provide deep and easy #introduction into #TS analysis.

Github: https://github.com/akshaykapoor347/Time-series-modeling-basics
Data Camp presentation: https://s3.amazonaws.com/assets.datacamp.com/production/course_5702/slides/chapter3.pdf

#beginner #novice #python #entrylevel

Modern Deep Learning Techniques Applied to Natural Language Processing

Online collaborative book

Link: https://nlpoverview.com/index.html
Github: https://github.com/omarsar/nlp_overview
ArXiV: https://arxiv.org/abs/1708.02709

#NLP #beginner #novice #entrylevel #DL

Yet another good intro into difference between artificial neural network and biological one.

If you're getting started in Data Science, you need to start with the basic building building block of Neural Networks - a Perceptron. To understand what it is, there's this good link to get started with.

Link: https://towardsdatascience.com/the-differences-between-artificial-and-biological-neural-networks-a8b46db828b7

#nn #entrylevel #beginner