From 00a513d059d6b55c276f40dea7ddcb1ea7e784ac Mon Sep 17 00:00:00 2001 From: ipcenas <47504178+ipcenas@users.noreply.github.com> Date: Tue, 29 Oct 2019 16:28:39 +0100 Subject: [PATCH 1/2] Added Succeeding with AI --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index f239bb20..2fc07c9f 100644 --- a/README.md +++ b/README.md @@ -243,6 +243,7 @@ Each day I take one subject from the list below, read it cover to cover, take no - [GitHub repository](https://github.com/ShangtongZhang/reinforcement-learning-an-introduction) - [ ] [Machine Learning with TensorFlow(MEAP)](https://www.manning.com/books/machine-learning-with-tensorflow) - [GitHub repository](https://github.com/BinRoot/TensorFlow-Book) +- [ ] [Succeeding with AI](https://www.manning.com/books/succeeding-with-ai) ## Kaggle knowledge competitions - [ ] [Kaggle Competitions: How and where to begin?](https://www.analyticsvidhya.com/blog/2015/06/start-journey-kaggle/) From aefb7ec72c760fd320020bd68fc1f79b41dc597a Mon Sep 17 00:00:00 2001 From: Sanyam Bhutani <16226196+init27@users.noreply.github.com> Date: Thu, 19 Dec 2019 10:19:20 +0530 Subject: [PATCH 2/2] Update README.md --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index f239bb20..f0fbf8f8 100644 --- a/README.md +++ b/README.md @@ -372,6 +372,9 @@ Each day I take one subject from the list below, read it cover to cover, take no - [Data Skeptic](http://dataskeptic.com/) - [This Week in Machine Learning & AI](https://twimlai.com/) - [Machine Learning Guide](http://ocdevel.com/podcasts/machine-learning) + +- ### Interviews with ML Practitioners, Researchers and Kagglers about their Joureny + - [Chai Time Data Science](https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x), [Audio](http://anchor.fm/chaitimedatascience), [Writeups](https://sanyambhutani.com/tag/chaitimedatascience/) - ### "More" advanced podcasts - [Partially Derivative](http://partiallyderivative.com/) @@ -380,7 +383,7 @@ Each day I take one subject from the list below, read it cover to cover, take no - ### Podcasts to think outside the box: - [Data Stories](http://datastori.es/) - + ## Communities - Quora - [Machine Learning](https://www.quora.com/topic/Machine-Learning)