A.I, Data and Software Engineering

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Recurrent neural network – predict monthly milk production

Recurrent neural network

In part 1, we introduced a simple RNN for time-series data. To continue, this article applies a deep version of RNN on a real dataset to predict monthly milk production. The data Monthly milk production: pounds per cow. Jan 1962 – Dec 1975. You can download the data using this link. Download: CSV file The data contains the production of 168 months (14 years). We will use an RNN to predict...

A really Cool data visualization: 3d globe in 2d space

3d-globe-animation

While generating data in 3d space for manifold learning, I went across a problem of distributing points evenly on a sphere. It is a non-trivial problem but found a good enough solution for such placement. Interestingly, it ends up with a really cool animation effect when I decided to implement it on a mobile app. Figure 1: First animation effect: Rotation The algorithm There are two qualitatively...

TF2.0 Warm-up exercises (forked from @chipHuyen Repo)

Petamind A.I

Heard of Ms @huyen chip for her notable yet controversial travelling books back in the day. I enjoy reading but I am not really into travel┬ámemoirs. Nevertheless, she did surprise everyone by her achievements by getting in Stanford, teaching TensorFlow, and then became a computer/data scientist. Her story is definitely very inspiring. For ones who don’t know about Ms Huyen, I added an...

New TensorFlow 2.0 vs 1.X – Quick note

Petamind A.I

TensorFlow 2.0 is out! Get hands-on practice at TF World, Oct 28-31. TensorFlow Ads Since the TF2.0 API reference lists have already been made publicly available, TF2.0 is still in RC.2 version. It is expected that the final release will be made available in the next few days (or weeks). What’s new in TF2.0: The obvious different – The version. In Colab, you can force using 2.0 by:...

A.I, Data and Software Engineering

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