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Aleksander Molak
Aleksander Molak

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Published in Towards Data Science

·Jan 8

Causal Python — Elon Musk’s Tweet, Our Googling Habits, and Bayesian Synthetic Control

Applying synthetic control with a Bayesian twist to quantify the impact of a tweet (using CausalPy) — October 2022 brought a lot of novelty to Twitter’s Headquarters in San Francisco (and a sink). Elon Musk, the CEO of Tesla and SpaceX became the new owner and CEO of the company on October 27. Some audiences welcomed the change warmly while others remained skeptical. A day later, on…

Python

11 min read

Causal Python — Elon Musk’s Tweet, Our Googling Habits & Bayesian Synthetic Control.
Causal Python — Elon Musk’s Tweet, Our Googling Habits & Bayesian Synthetic Control.
Python

11 min read


Published in Towards Data Science

·Dec 11, 2022

Causal Python — Level Up Your Causal Discovery Skills in Python (2023)

…and unlock the potential of the best Causal Discovery package in Python! — Introduction The recent surge in interest in causality-related topics in Python has led to a wealth of resources making a decision what to focus on challenging. For instance, many resources on the internet describe a popular NOTEARS algorithm (Zheng et al., 2018) as the “state-of-the-art structure learning method”, yet NOTEARS has…

Python

15 min read

Causal Python — Level Up Your Causal Discovery Skills in Python (2023)
Causal Python — Level Up Your Causal Discovery Skills in Python (2023)
Python

15 min read


Oct 17, 2022

Yes! Six Causality Books That Will Get You From Zero to Advanced (2023)

…and you can get 3 of them completely for free if you want! 🤗 — Introduction Recent years brought a sharp increase in interest in causal methods in the research community and in the industry. One of the challenges that people entering the field face is a lack of standardized resources and terminology. Causality research has been scattered and divided into sub-fields for decades. One of…

Causality

9 min read

Yes! Six Causality Books That Will Get You From Zero to Advanced (2023)
Yes! Six Causality Books That Will Get You From Zero to Advanced (2023)
Causality

9 min read


Published in Towards Data Science

·Sep 27, 2022

Causal Python — 3 Simple Techniques to Jump-Start Your Causal Inference Journey Today

Learn 3 techniques for causal effect identification and implement them in Python without losing months, weeks or days for research — If you’re reading this you’ve probably been in data science for some 2–5 years now. You have most likely heard about causality before, maybe even read a book or two on the topic, yet if you don’t feel confident or you’re missing some clarity on how to grab these concepts…

Python

12 min read

Causal Python — 3 Simple Techniques to Jump-Start Your Causal Inference Journey Today
Causal Python — 3 Simple Techniques to Jump-Start Your Causal Inference Journey Today
Python

12 min read


May 2, 2022

Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere — a review (Polish)

A Polish translation of an article, that we wrote with Mike Erlihson, PhD as a part of #DeepNightLearners series. — Scroll down for English and Hebrew versions. Other language versions: - English (original) - Hebrew Współautorem tego artykułu jest Mike Erlihson. W tłumaczeniu pomógł Mateusz Modrzejewski ❤️ W zasadzie dowolne dane mogę być reprezentowane jako wektor w ciągłej przestrzeni reprezentacji. Często jednak wektory dla różnych punktów danych koncentrują się w…

Unsupervised Learning

7 min read

Understanding Contrastive Representation Learning through Alignment and Uniformity on the…
Understanding Contrastive Representation Learning through Alignment and Uniformity on the…
Unsupervised Learning

7 min read


Feb 4, 2022

Three amazing data science books to read in 2023 (if you didn’t manage in 2022)

…and you can get them for free if you want! ❤️ — Introduction 2022 was a truly amazing year for the machine learning community worldwide! Many long-awaited titles have been released, including new editions of all-time classics. In this post I want to share with you three 2022 titles that I believe are especially worth reading (not only) this year. At the end…

Machine Learning

5 min read

Three amazing data science books to read in 2023 (if you didn’t manage in 2022)
Three amazing data science books to read in 2023 (if you didn’t manage in 2022)
Machine Learning

5 min read


Published in Towards Data Science

·Nov 26, 2021

Modeling uncertainty in neural networks with TensorFlow Probability

Part 4: Going fully probabilistic¹ — This series is a brief introduction to modeling uncertainty using TensorFlow Probability library. I wrote it as a supplementary material to my PyData Global 2021 talk on uncertainty estimation in neural networks. Articles in the series: Part 1: An Introduction Part 2: Aleatoric uncertainty Part 3: Epistemic uncertainty Part 4…

Bayesian Machine Learning

5 min read

Modeling uncertainty in neural networks with TensorFlow Probability
Modeling uncertainty in neural networks with TensorFlow Probability
Bayesian Machine Learning

5 min read


Published in Towards Data Science

·Nov 19, 2021

Modeling uncertainty in neural networks with TensorFlow Probability

Part 3: Epistemic uncertainty — This series is a brief introduction to modeling uncertainty using TensorFlow Probability library. I wrote it as a supplementary material to my PyData Global 2021 talk on uncertainty estimation in neural networks. Articles in the series: Part 1: An Introduction Part 2: Aleatoric uncertainty Part 3: Epistemic uncertainty Part 4…

Python

7 min read

Modeling uncertainty in neural networks with TensorFlow Probability
Modeling uncertainty in neural networks with TensorFlow Probability
Python

7 min read


Published in Towards Data Science

·Nov 12, 2021

Modeling uncertainty in neural networks with TensorFlow Probability

Part 2: Aleatoric uncertainty — This series is a brief introduction to modeling uncertainty using TensorFlow Probability library. I wrote it as a supplementary material to my PyData Global 2021 talk on uncertainty estimation in neural networks. Articles in the series: Part 1: An Introduction Part 2: Aleatoric uncertainty Part 3: Epistemic uncertainty Part 4…

Bayesian Machine Learning

8 min read

Modeling uncertainty in neural networks with TensorFlow Probability
Modeling uncertainty in neural networks with TensorFlow Probability
Bayesian Machine Learning

8 min read


Published in Towards Data Science

·Nov 3, 2021

Modeling uncertainty in neural networks with TensorFlow Probability

Part 1: An introduction — This series is a brief introduction to modeling uncertainty using TensorFlow Probability library. I wrote it as a supplementary material to my PyData Global 2021 talk on uncertainty estimation in neural networks. Articles in the series: Part 1: An Introduction Part 2: Aleatoric uncertainty Part 3: Epistemic uncertainty Part 4…

Python

6 min read

Modeling uncertainty in neural networks with TensorFlow Probability
Modeling uncertainty in neural networks with TensorFlow Probability
Python

6 min read

Aleksander Molak

Aleksander Molak

668 Followers

ML Rsrch+Eng. Causality, NLP & Probabilistic Modeling || Causal book: https://causalpython.io || Educator @ https://lespire.io

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