**Reading time:**

**3 minutes**

### Best links of the week from August 2nd to September 21st

#### Links

- Maximum Likelihood Estimates by Jeremy Orloff and Jonathan Bloom.
- Moravec’s paradox at Wikipedia.
- Parrondo’s paradox at Wikipedia.
- R-squared Cautions at STAT 462 (Applied Regression Analysis), PennState University.
- Spearman’s correlation.
- CausalCity: Introducing a high-fidelity simulation with agency for advancing causal reasoning in machine learning at Microsoft Research Blog.
- The Most Dangerous Equation at American Scientist. More here and here.
- One day course on causal inference, MPI-EVA 9 September 2021 at Richard McElreath‘s GitHub.
- The cost of dichotomising continuous variables, published in BMJ, at PubMed Central.
- How Computationally Complex Is a Single Neuron? at QuantaMagazine.
- Focus on Peer Review Course at Nature Masterclasses.

#### Blog posts

- What Is TF-IDF? at MonkeyLearn.
- The Beginner’s Guide to Text Vectorization at MonkeyLearn.
- Naive Bayes and Text Classification at Sebastian Raschka.
- Neural Network: Architecture, Components & Top Algorithms at UpGrad.
- Why Initialize a Neural Network with Random Weights? at Machine Learning Mastery.
- Hacks, IA’s e manipulação humana at Portal Deviante.
- Neural Network Models in R at DataCamp Tutorial.
- Demystifying Mathematical Concepts for Deep Learning at DataCamp Tutorial.
- Deduce the Number of Layers and Neurons for ANN at DataCamp Tutorial.
- A Gentle Introduction to Exploding Gradients in Neural Networks at Machine Learning Mastery.
- How to Fix the Vanishing Gradients Problem Using the ReLU at Machine Learning Mastery.
- A Gentle Introduction to the Rectified Linear Unit (ReLU) at Machine Learning Mastery.
- The New Base Pipe at MyKo101.
- ETL vs ELT Explained at The Grouparoo Blog.
- The Mathematics Behind Deep Learning by Trist’n Joseph at Towards Data Science.
- The Unreasonable Ineffectiveness of Deep Learning on Tabular Data by Paul Tune at Towards Data Science.
- SHAP Values Explained Exactly How You Wished Someone Explained to You by Samuele Mazzanti at Towards Data Science.
- Black-Box models are actually more explainable than a Logistic Regression by Samuele Mazzanti at Towards Data Science.
- Increasing developer happiness with GitHub code scanning at GitHub blog.
- What can Avengers: Endgame teach us about Git? at Lj Miranda‘s Blog.

#### Videos

- StatQuest: Maximum Likelihood, clearly explained!!! at StatQuest with Josh Starmer.
- Maximum Likelihood for the Exponential Distribution, Clearly Explained! V2.0 at StatQuest with Josh Starmer.
- Maximum Likelihood for the Binomial Distribution, Clearly Explained!!! at StatQuest with Josh Starmer.
- Parte 1 – Regressão Linear – É a sua chance! Agora ou nunca! – Prof. Adriana Silva at EstaTiDados.
- Parte 2 – Regressão Linear – É a sua chance! Agora ou nunca! – Prof. Adriana Silva at EstaTiDados.
- Parte 3 – Regressão Logística – É a sua chance! Agora ou nunca! – Prof. Adriana Silva at EstaTiDados.
- Estreia da Série Teoria de Conjuntos para Estatística – Teoria de conjuntos #1 at A Ciência da Estatística.
- Axiomas da EXTENSÃO e da ESPECIFICAÇÃO (Pertencimento, Igualdade e Inclusão) -Teoria de Conjuntos #2 at A Ciência da Estatística.
- Axiomas do PAR e da UNIÃO (união, interseção, diferença, Complementar) – Teoria de Conjuntos #3 at A Ciência da Estatística.
- Axioma da POTÊNCIA (Conjuntos das partes, produtos cartesianos e relações) – Teoria de conjuntos #4 at A Ciência da Estatística.
- FUNÇÕES injetoras, sobrejetoras e bijetoras (IMAGEM e IMAGEM INVERSA) – Teoria de conjuntos #5 at A Ciência da Estatística.
- Cost Function in Neural Network | Types of Cost function we use in different applications at Coding Lane.
- What is Activation function in Neural Network ? Types of Activation Function in Neural Network at Coding Lane.
- Mas o que *é* uma Rede Neural? | Deep learning, capítulo 1 at 3Blue1Brown‘s YouTube channel.
- Causal Discovery Part 1 by Bernhard Schölkopf at MLSS Africa’s YouTube channel.
- Causal Discovery Part 2 by Bernhard Schölkopf at MLSS Africa’s YouTube channel.
- Spearman’s Rank-Order Correlation at Laerd Statistics.
- Spearman’s Rank-Order Correlation using SPSS Statistics at Laerd Statistics.
- An Ode To R-Squared by Callum Ballard at Towads Data Science.
- Spearman’s Rank Correlation part 1 at ECOHOLICS – Largest Platform for Economics.
- Spearman’s Rank Correlation part 2 at ECOHOLICS – Largest Platform for Economics.
- Spearman’s Rank Correlation part 3 at ECOHOLICS – Largest Platform for Economics.
- Machine Learning Experiments with DVC (Hands-On Tutorial!) at DVCorg‘s YouTube channel.
- Checkpoints at DVCorg‘s YouTube channel.
- Experiments at DVCorg‘s YouTube channel.
- Deep Learning Basics: Introduction and Overview at Lex Fridman‘s YouTube channel.

#### Positions available

- PostDoc in Protein Biochemistry at MPI CBG.
- PhD student in Computational Biology at MPI CBG.
- Postdoctoral Position in Computational Biology at MPI CBG.
- Postdoctoral Position in Cell Biology at MPI CBG.
- PhD scholarship in “AI for electricity market design” at DTU.
- Engineer R&D at SteelSeries.
- Postdoctoral opportunity on (hierarchical) multi-agent reinforcement learning at Northeastern University.
- Machine Learning Fairness Research PhD Intern at Tiktok.
- Assistant Professor – Computational Linguistics at University of Toronto Scarborough.
- Several postdoctoral research positions in Bayesian optimization and/or simulation-based optimization in Montreal.
- Postdoc in Computer Vision/Deep Learning: video monitoring of insect pollinators at the University of Puerto Rico.
- Open positions for AI professors at FHWS.
- PhD scholarship in NLP at James Cook University.
- Assistant Professor – AI at Iowa State University.
- Open Postdoc Position Medical AI at Med Uni Graz.
- Staff Data Scientist at FireEye.
- Cientista de Dados | Big Data & AI at Grupo Globo.
- Pessoa Engenheira de Dados | Big Data & AI at Grupo Globo.
- Pessoa Engenheira de Machine Learning | Big Data & AI at Grupo Globo.
- Analista de Dados Sênior at OLX.