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

​​Modeling Price with Regularized Linear Model & #XGBoost

Great example of applicable research for #production #ML.

Link: https://www.kdnuggets.com/2019/05/modeling-price-regularized-linear-model-xgboost.html

#novice #entrylevel

Machine Learning for Everyone.

The best general intro post about Machine Learning, covering everything you need to know not to get overxcited about SkyNet and to get general understanding of all #ML / #AI hype. You can surely save this post into «Saved messages» and forward it to your friends to make them familiar with the subject

Link: https://vas3k.com/blog/machine_learning/

#entrylevel #novice #general

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

Useful and practical post on pandas indexing

Link: https://www.shanelynn.ie/select-pandas-dataframe-rows-and-columns-using-iloc-loc-and-ix/

#beginner #pandas #practical #novice #entrylevel

​​🥇Parameter optimization in neural networks.

Play with three interactive visualizations and develop your intuition for optimizing model parameters.

Link: https://www.deeplearning.ai/ai-notes/optimization/

#interactive #demo #optimization #parameteroptimization #novice #entrylevel #beginner #goldcontent #nn #neuralnetwork

Great collection and reviews for top online machine and deep learning courses

Post covers short reviews and suggested order in which course could be taken, along with the links at great prerequisites.

Link: http://thegrandjanitor.com/2016/08/15/learning-deep-learning-my-top-five-resource/

#DL #ML #MOOC #novice #entrylevel

​​LSTM on Amazon Food Reviews using Google Collaboratory

Article describing how to build easy and small #LSTM network to predict review score based on its text, using #GoogleCollab. This is an #entrylevel post, useful if you have medium experience in #NLP.

Link: https://medium.com/@theodoxbolt/lstm-on-amazon-food-reviews-using-google-collaboratory-34b1c2eceb80

#novice

Great collections of Data Science learning materials

The list includes free books and online courses on range of DS-related disciplines:

Machine learning (#ML)
Deep Learning (#DL)
Reinforcement learning (#RL)
#NLP

Tutorials on #Keras, #Tensorflow, #Torch, #PyTorch, #Theano

Notable researchers, papers and even #datasets. It is a great place to start reviewing your knowledge or learning something new.

Link: https://hackmd.io/@chanderA/aiguide

#wheretostart #entrylevel #novice #studycontent #studymaterials #books #MOOC #meta

🎓CS224W: Machine Learning with Graphs

Great course from #Stanford. You still on time to jump at studying from one of the best schools.

Students are introduced to machine learning techniques and data mining tools apt to reveal insights on the social, technological, and natural worlds, by means of studying their underlying network structure and interconnections.

Topics include: robustness and fragility of food webs and financial markets; algorithms for the World Wide Web; graph neural networks and representation learning; identification of functional modules in biological networks; disease outbreak detection.

Link: http://cs224w.stanford.edu
Videos link: http://snap.stanford.edu/class/cs224w-videos-2019/

#MOOC #entrylevel #wheretostart

​​GANs from Scratch 1: A deep introduction.

Great introduction and tutorial. With code in PyTorch and TensorFlow

Link: https://medium.com/ai-society/gans-from-scratch-1-a-deep-introduction-with-code-in-pytorch-and-tensorflow-cb03cdcdba0f

#tensorflow #pytorch #GAN #tutorial #entrylevel #novice #wheretostart

Classification and Loss Evaluation - Softmax and Cross Entropy Loss

Nice notes on softmax cross entropy loss and how to implement it in numpy.

Link: https://deepnotes.io/softmax-crossentropy

#nn #entrylevel #wheretostart

Big scandal on popular YouTuber ML course

Siraj Raval, who raised his audience on devliering various YouTube videos, explaning #ML and #DL concepts as long with interviews with leading persons, launched his own course, but failed to provide much value.

His course was built on open and free tutorials, created by passionate enthusiasts, but he failed to attribute them properly and charged money for ununique content without any proper support for students.

He also oversold his course and tried to hide that from students, claiming to provide personal feedbacks, but failing to do so due to being too greedy.


Most of the best online courses and study programms are available online and for free, including those, we gathered here on our channel and attributed with hastags #wheretostart #entrylevel #MOOC #tutorial. Feel free to click these hashtags and browse for best available resources to start learning data science.

Link: https://www.theregister.co.uk/AMP/2019/09/27/youtube_ai_star

AMA today at 15:00 GMT (in 4 hours). In a couple of hours we will publish link to private chat for AMA session.

Stay tuned, prepare your questions. Please do not ask trivial and gramatically incorrect questions like 'where to start data science'.
First of all, use search, we have nice collections of resources for starting a DS career, tagged with #wheretostart #entrylevel #novice. Secondly, pay respect to our guest and ask questions more relevant to his area of experise.

Simple comic on how #ML works from #Google

Make sure you save the link (or this message) to show it to people without great technical background for it is one of the best and clear explanations there is.

Link: https://cloud.google.com/products/ai/ml-comic-1/

#wheretostart #entrylevel #novice #explainingtochildren

Implementing Transfer Learning in PyTorch

Fine-tuning and feature extraction with PyTorch

Link: https://medium.com/analytics-vidhya/transfer-learning-in-pytorch-f7736598b1ed

#PyTorch #novice #entrylevel #beginner

All the vector algebra you need for understanding neural networks

Article contains great explanations and description of matrix calculus you need to know and understand to really grok neural networks.

Link: https://explained.ai/matrix-calculus/index.html

#WhereToStart #entrylevel #novice #base #DL #nn

P-value, explained, one more time with demos

Article includes not only great explanation of what is #pvalue, but how it works and how it can be used to make a correct conclusions.

Link:https://www.freecodecamp.org/news/what-is-statistical-significance-p-value-defined-and-how-to-calculate-it/

#entrylevel #dsformanagers #tutorial #explained #interactive #statistics

​​Ultimate post on where to start learning DS

Most common request we received through the years was to share insights and advices on how to start career in data science and to recommend decent cources. Apparently, using hashtag #wheretostart wasn't enough so we were sharing some general advices.

So we assembled a through guide on how to start learning machine learning and created another #ultimatepost (in a form of a github repo, so it will be keep updated and anyone can submit worthy piece of advice to it).

We welcome you to share your stories and advices on how to start rolling into data science, as well as to spread the link to the repo to those your friends who might benefit from it.

Link: Ultimate post

#entrylevel #beginner #junior #MOOC #learndatascience #courses #mlcourse #opensource