handson-ml2 | Jupyter notebooks that walk you through the fundamentals | Machine Learning library

 by   ageron Jupyter Notebook Version: Current License: Apache-2.0

kandi X-RAY | handson-ml2 Summary

kandi X-RAY | handson-ml2 Summary

handson-ml2 is a Jupyter Notebook library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Jupyter, Pandas applications. handson-ml2 has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

            kandi-support Support

              handson-ml2 has a medium active ecosystem.
              It has 24957 star(s) with 11931 fork(s). There are 638 watchers for this library.
              It had no major release in the last 6 months.
              There are 194 open issues and 295 have been closed. On average issues are closed in 24 days. There are 6 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of handson-ml2 is current.

            kandi-Quality Quality

              handson-ml2 has 0 bugs and 0 code smells.

            kandi-Security Security

              handson-ml2 has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              handson-ml2 code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              handson-ml2 is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              handson-ml2 releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.
              It has 13 lines of code, 1 functions and 1 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            handson-ml2 Key Features

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            handson-ml2 Examples and Code Snippets

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            Community Discussions


            Custom environment using TFagents
            Asked 2021-Jun-02 at 22:36

            I am trying to learn a custom environment using the TFAgents package. I am following the Hands-on-ML book (Code in colab see cell 129). My aim is to use DQN agent on a custom-written grid world environment.

            Grid-World environment:



            Answered 2021-Jun-02 at 22:36

            You cannot use TensorSpec with PyEnvironment class objects, this is why your attempted solution does not work. A simple fix should be to use the original code

            Source https://stackoverflow.com/questions/65743558


            What does urllib.request.urlretrieve do if not returned
            Asked 2021-Apr-12 at 14:50

            From the python document, it is mentioned that urllib.request.urlretrieve returns a tuple and will be used to open file as shown in Code-A below.

            However in the example Code-B. The urllib.request.urlretrieve does not return but the code will fail without it. Please help clarify what does urllib.request.urlretrieve doing in Code B. THanks

            Code A



            Answered 2021-Apr-12 at 14:39

            The retrieve() method is used to save web content from url (eg csv,images etc) In your case it is saving the housing data saved up in the url. You can check the docs [here][1]

            Source https://stackoverflow.com/questions/67060306


            Understanding and Evaluating different methods in Reinforcement Learning
            Asked 2021-Jan-09 at 03:53

            I have been trying to implement the Reinforcement learning algorithm on Python using different variants like Q-learning, Deep Q-Network, Double DQN and Dueling Double DQN. Consider a cart-pole example and to evaluate the performance of each of these variants, I can think of plotting sum of rewards to number of episodes (attaching a picture of the plot) and the actual graphical output where how well the pole is stable while the cart is moving.

            But these two evaluations are not really of interest in terms to explain the better variants quantitatively. I am new to the Reinforcement learning and trying to understand if any other ways to compare different variants of RL models on the same problem.

            I am referring to the colab link https://colab.research.google.com/github/ageron/handson-ml2/blob/master/18_reinforcement_learning.ipynb#scrollTo=MR0z7tfo3k9C for the code on all the variants of cart pole example.



            Answered 2021-Jan-09 at 03:53

            You can find the answer in research paper about those algorithms, because when a new algorithm been proposed we usually need the experiments to show the evident that it have advantage over other algorithm.

            The most commonly used evaluation method in research paper about RL algorithms is average return (note not reward, return is accumulated reward, is like the score in game) over timesteps, and there many way you can average the return, e.g average wrt different hyperparameters like in Soft Actor-Critic paper's comparative evaluation average wrt different random seeds (initialize the model):

            Figure 1 shows the total average return of evaluation rolloutsduring training for DDPG, PPO, and TD3. We train fivedifferent instances of each algorithm with different randomseeds, with each performing one evaluation rollout every1000 environment steps. The solid curves corresponds to themean and the shaded region to the minimum and maximumreturns over the five trials.

            And we usually want compare the performance of many algorithms not only on one task but diverse set of tasks (i.e Benchmark), because algorithms may have some form of inductive bias for them to better at some form of tasks but worse on other tasks, e.g in Phasic Policy Gradient paper's experiments comparison to PPO:

            We report results on the environments in Procgen Benchmark (Cobbe et al.,2019). This benchmark was designed to be highly diverse, and we expect improvements on this benchmark to transfer well to many other RL environment

            Source https://stackoverflow.com/questions/65636703


            Why shuffling the data like this leads to a poor accuracy
            Asked 2020-Dec-14 at 17:01

            I am reading the book "Hands-On Machine Learning" and I have a problem with exercise 9 of chapter 13, the exercise is as follows:

            a. Load the Fashion MNIST dataset (introduced in Chapter 10); split it into a training set, a validation set, and a test set; shuffle the training set; and save each dataset to multiple TFRecord files. Each record should be a serialized Example protobuf with two features: the serialized image (use tf.io.serialize_tensor() to serialize each image), and the label.

            b. Then use tf.data to create an efficient dataset for each set. Finally, use a Keras model to train these datasets, including a preprocessing layer to standardize each input feature.

            You can find the exercise with the solution at the end of this notebook: https://github.com/ageron/handson-ml2/blob/master/13_loading_and_preprocessing_data.ipynb

            I loaded the data like this:



            Answered 2020-Dec-14 at 17:01

            Because you are shuffling only the input data (X_train) without applying the same shuffling to the corresponding labels y_train. You should shuffle both together:

            Source https://stackoverflow.com/questions/65292999


            Python 3.8.3 "File-not-found" message
            Asked 2020-Oct-05 at 05:49

            I am currently studying the book "Hands-On Machine Learning with Scikit-Learn, Keras and TensorFlow". I tried running the following example, without success however. The link is working, pandas is installed correctly, os, tarfile and urllib are system packages. Still, I get the error message below (tried Jupyter & Spyder):



            Answered 2020-Oct-05 at 05:49

            The local file "datasets/housing/housing.csv" is created only when you call

            Source https://stackoverflow.com/questions/64202986


            Error in using DataFrameMapper() for PolynomialFeature() in sklearn
            Asked 2020-Sep-19 at 16:36

            For housing data set, I am trying to use DataFrameMapper() from sklearn_pandas to apply polynomial features on selected columns.

            My code:



            Answered 2020-Sep-19 at 16:36
            • From the documentation
              • The difference between specifying the column selector as 'column' (as a simple string) and ['column'] (as a list with one element) is the shape of the array that is passed to the transformer. In the first case, a one dimensional array will be passed, while in the second case it will be a 2-dimensional array with one column, i.e. a column vector.
            • All of the columns must be passed with the same type of column selector.
              • In this case, a list, since there's a list of non-transformed columns to keep.

            Source https://stackoverflow.com/questions/63970578


            MemoryError: Unable to allocate MiB for an array with shape and data type, when using anymodel.fit() in sklearn
            Asked 2020-Sep-04 at 06:51

            Getting this memory error. But the book/link I am following doesn't get this error.

            A part of Code:



            Answered 2020-Jul-10 at 19:35

            The message is straight forward, yes, it has to do with the available memory.

            359 MiB = 359 * 2^20 bytes = 60000 * 784 * 8 bytes

            where MiB = Mebibyte = 2^20 bytes, 60000 x 784 are the dimensions of your array and 8 bytes is the size of float64.

            Maybe the 3.1gb free memory is very fragmented and it is not possible to allocate 359 MiB in one piece?

            A reboot may be helpful in that case.

            Source https://stackoverflow.com/questions/62839068


            Powershell set a variable and print but nothing
            Asked 2020-Sep-01 at 03:53
            SET ML_PATH=E:\Workspace\Handson-ml2
            echo $ML_PATH


            Answered 2020-Sep-01 at 03:53

            You can define a variable in PowerShell using the $varname = syntax:

            Source https://stackoverflow.com/questions/63680632


            Installing Tensorflow 2 gets a dll failed to load in pywrap_tensorflow.py
            Asked 2020-Jul-26 at 16:09

            I have had problems here, here and there installing TensorFlow 2 over the last year or so. So I am trying Miniconda.

            I have an AMD Radeon hd 6670 and an AMD Radeon hd 6450.

            I just downloaded Miniconda and made an environment and did a pip install --upgrade tensorflow in a Miniconda prompt on Windows 8.1 and got TensorFlow 2.2.

            When I try to import tensorflow I get the stack trace below.

            I did download Visual Studio to get the latest redistributebles (I think).

            seems like this occurs near this line: from tensorflow.python.pywrap_tensorflow_internal import *

            Edit 1: I used this yaml file for python 3.6 (the other was 3.7), but it produced the same error.

            Edit 2: I upgraded to Conda 4.8.3 and Python 3.7 (in the yaml file) and got the same error. This is the line in pywrap internal that shows the problem:



            Answered 2020-Jul-26 at 16:09
            Status Quo

            I ran into a comparable problem (this is the furthest i got) reproducibly on two machines. Some of the discussed issues seems to be known for example here: 1 2 3 4. Not only to reproduce 2, it makes sense to also start using virtual environments in order to test multiple tf versions. This can be achieved like this: (link for virtualenv on windows)

            Source https://stackoverflow.com/questions/62376660


            How to execute only particular part of the scikit-learn pipeline?
            Asked 2020-Jun-03 at 21:02

            Below is part of the code that is relevant to the question. If there is a need for full code, here is a full reproducible code that downloads data too: https://github.com/ageron/handson-ml2/blob/master/02_end_to_end_machine_learning_project.ipynb

            I have a pipeline:



            Answered 2020-Jun-03 at 20:02

            FeatureUnion can do the trick:

            Source https://stackoverflow.com/questions/62180278

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install handson-ml2

            Start by installing [Anaconda](https://www.anaconda.com/distribution/) (or [Miniconda](https://docs.conda.io/en/latest/miniconda.html)), [git](https://git-scm.com/downloads), and if you have a TensorFlow-compatible GPU, install the [GPU driver](https://www.nvidia.com/Download/index.aspx), as well as the appropriate version of CUDA and cuDNN (see TensorFlow’s documentation for more details).


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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