lightwood
Lightwood is Legos for Machine Learning. (by mindsdb)
probability
Probabilistic reasoning and statistical analysis in TensorFlow (by tensorflow)
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lightwood | probability | |
---|---|---|
2 | 10 | |
420 | 4,128 | |
3.8% | 2.0% | |
9.2 | 9.3 | |
6 days ago | 13 days ago | |
Python | Jupyter Notebook | |
GNU General Public License v3.0 only | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
lightwood
Posts with mentions or reviews of lightwood.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-02-19.
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[D] What would a good ML take home test look like for you?
Create a very detailed issue about this (bonus points, you can use the same thing for all candidates to have a fair evaluation). Here's an example.
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Launch HN: MindsDB (YC W20) – Machine Learning Inside Your Database
3. A decoder that is trained to generate images takes that representation and generates an image1.
Note: above is a good illustrative example, in practice, we're good with outputting dates, numerical, categories, tags and time-series (i.e. predicting 20 steps ahead). We haven't put much work into image/text/audio/video outputs
You should be able to find more details about how we do this in the docs and most of the heavy lifting happens in the lightwood repo, the code for that is fairly readable I hope: https://github.com/mindsdb/lightwood
probability
Posts with mentions or reviews of probability.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-06-17.
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How often do you see Bayesian Statistics or Stan in the DS world? Essential skill or a nice to have?
TensorFlow-Probability
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DevOps may have cheated death, but do we all need to work for the king of the underworld?
If you are interested in probabilistic programming, causal modeling and bayesian graphical modeling, I recommend checking out Tensorflow Probability (https://www.tensorflow.org/probability).
- [P] Any good resources which can help me with Multivariate Time Series Forecasting using Probabilistic Machine Learning?
- Bayesian Hierarchical Models for algorithmic trading?
- Is anyone here working in uncertainty estimation in neural networks?
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[Q] Sociology PhD Student with Interest in Statistical Programming/Data Science
As others have said, R for academia, Python for industry. However, i'd also throw Stan into the mix, along with other PPL frameworks like Tensorflow Probability and Pyro. The latter two will require you to learn Python first, though.
- [D] Bayesian Regression or GPs in production?
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What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing
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Problem in installing tensorflow on Raspberry Pi 4b
2021-03-20 20:09:56.451490: E tensorflow/core/platform/hadoop/hadoopfile_system.cc:132] HadoopFileSystem load error: libhdfs.so: cannot open shared object file: No such file or directory WARNING:tensorflow:From /home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/ops/distributions/distribution.py:265: ReparameterizationType.init_ (from tensorflow.python.ops.distributions.distribution) is deprecated and will be removed after 2019-01-01. Instructions for updating: The TensorFlow Distributions library has moved to TensorFlow Probability (https://github.com/tensorflow/probability). You should update all references to use tfp.distributions instead of tf.distributions. WARNING:tensorflow:From /home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflowcore/python/ops/distributions/bernoulli.py:169: RegisterKL.init_ (from tensorflow.python.ops.distributions.kullbackleibler) is deprecated and will be removed after 2019-01-01. Instructions for updating: The TensorFlow Distributions library has moved to TensorFlow Probability (https://github.com/tensorflow/probability). You should update all references to use tfp.distributions instead of tf.distributions. ERROR thonny.backend: PROBLEM WITH THONNY'S BACK-END Traceback (most recent call last): File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 1240, in wrapper result = method(self, args, *kwargs) File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 1227, in wrapper return method(self, args, *kwargs) File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 1297, in _execute_prepared_user_code exec(statements, global_vars) File "/home/pi/Desktop/security/security_system_v2.py", line 10, in import tensorflow as tf File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow/init.py", line 98, in from tensorflow_core import * File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/init.py", line 28, in from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "", line 1019, in _handle_fromlist File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow/init.py", line 50, in __getattr_ module = self.load() File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow/init.py", line 44, in _load module = _importlib.import_module(self.name) File "/usr/lib/python3.7/importlib/init.py", line 127, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/init.py", line 88, in from tensorflow.python import keras File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/keras/init.py", line 26, in from tensorflow.python.keras import activations File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/keras/init.py", line 26, in from tensorflow.python.keras import activations File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/keras/activations.py", line 23, in from tensorflow.python.keras.utils.generic_utils import deserialize_keras_object File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/keras/utils/init.py", line 34, in from tensorflow.python.keras.utils.io_utils import HDF5Matrix File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/tensorflow_core/python/keras/utils/io_utils.py", line 30, in import h5py File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "/home/pi/.virtualenvs/cv/lib/python3.7/site-packages/h5py/init_.py", line 25, in from . import _errors File "/usr/lib/python3/dist-packages/thonny/plugins/cpython/cpython_backend.py", line 314, in _custom_import module = self._original_import(args, *kw) File "h5py/_errors.pyx", line 1, in init h5py._errors ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 44 from C header, got 40 from PyObject
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Tensorflow not utilizing GPU with eager execution
You implemented much of your model yourself. I have come across this GItHub issue recently where people reported a large slowdown when they were running their self-built models eagerly. It seems to be somewhat similar to yours. One answer (this one: https://github.com/tensorflow/probability/issues/629#issuecomment-551875968) seems to allow people to achieve speedups.
What are some alternatives?
When comparing lightwood and probability you can also consider the following projects:
MindsDB - The platform for customizing AI from enterprise data
pyro - Deep universal probabilistic programming with Python and PyTorch