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machine-learning in Python Reviews & Product Details - Page 3

machine-learning in Python Overview

What is machine-learning in Python?

machine learning support vector machine (SVMs), and support vector regression (SVRs) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis.

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Product Description

machine learning support vector machine (SVMs), and support vector regression (SVRs) are supervised learning models with associated learning algorithms that analyze data and recognize patterns, used for classification and regression analysis.


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machine-learning in Python

Description

The repository "machine-learning" by jeff1evesque on GitHub provides a comprehensive solution for implementing machine learning algorithms in Python. This project offers a robust framework designed to facilitate the development of machine learning models, emphasizing ease of use and scalability. It likely includes various utilities and pre-built components to assist users in creating and training models, handling data preprocessing, evaluation, and optimization tasks. As an open-source project, it encourages collaboration and contributions from developers and researchers interested in enhancing or extending its functionality. You can access the repository and its resources at https://github.com/jeff1evesque/machine-learning.

Recent machine-learning in Python Reviews

Komal A.
KA
Komal A.Enterprise (> 1000 emp.)
4.5 out of 5
"Pandas With Pyton"
I like that Python offers a rich ecosystem of libraries like TensorFlow, scikit-learn, and PyTorch, making it easy to implement and experiment with...
Mikhail I.
MI
Mikhail I.Enterprise (> 1000 emp.)
4.0 out of 5
"Director of Engineering - Oracle"
- Makes Data Preparation and exploration easy, specially at initial stage - No need for data extraction. Can work with the data in DB - Pipeline ...
Kunal M.
KM
Kunal M.Mid-Market (51-1000 emp.)
5.0 out of 5
"My review on machine learning with python"
The thing I like best about machine learning with python is it provides extensive libraries and framework which make our work easy. It's has one of...

Pricing Insights

Averages based on real user reviews.

Time to Implement

1 month

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35 machine-learning in Python Reviews

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35 machine-learning in Python Reviews
4.7 out of 5
35 machine-learning in Python Reviews
4.7 out of 5

machine-learning in Python Pros and Cons

How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
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G2 reviews are authentic and verified.
JS
Mid-Market(51-1000 emp.)
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What do you like best about machine-learning in Python?

Its easy to use. Lots of documentation online. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Currently, nothing. I prefer it to Matlab or R. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

Learn and use it as much as you can. This is definitely going to be used in the future as well. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

It depends what comes my way. I have done forecasting of stocks, developed churn prediction models for retail industry. Review collected by and hosted on G2.com.

Savannah L.
SL
Post-Baccalaureate IRTA
Research
Enterprise(> 1000 emp.)
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What do you like best about machine-learning in Python?

There are so many well-documented, common-sense, easily implementable python scripts and packages for machine learning. Scikit learn has some amazing tutorials, for concept learning, function learning or “predictive modeling”, and clustering and finding predictive patterns. With the language of python itself, it is easy to understand how to utilize the Kmeans algorithm, and implement aspects of machine learning with your own data. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Getting started can be difficult! Tutorials can be hard to find, especially if you aren't used to using open-source languages like python. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

Big data analysis to measure outcomes for our smartphone app intervention Review collected by and hosted on G2.com.

Verified User in Aviation & Aerospace
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Enterprise(> 1000 emp.)
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What do you like best about machine-learning in Python?

Python is one of the most popular programming languages for solving the problems associated with machine learning. Python libraries like Keras, Theanos, TensorFlow, and Scikit-Learn have made programming machine learning relatively easy. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Sometimes because of data Python IDE gets hanged. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

Machine learning is best used in Python because of ML libraries and especially for data visualization. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

I use machine learning to build classification models to solve industrial problems. I have realized that it is easy to interpret and understandable. Easy to create a confusion matrix which is used for getting classification accuracy. Review collected by and hosted on G2.com.

Verified User in Medical Practice
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What do you like best about machine-learning in Python?

Machine learning with Python is very much easy to set up. Once you have download Python, assuming if you download with Spyder and Anaconda, everything will be pre-packaged.

For people with amataeur coding knowledge like me, whenever I hit a brick wall, I’m able to go online and find solutions. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Unlike Tableau, there is no official platform, at least I couldn’t find one. Plus there’s way too many packages for machine learning. You need to do your research to know which is suitable for your scenario. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

Natural lanaguage processing, text classification. Review collected by and hosted on G2.com.

AS
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What do you like best about machine-learning in Python?

Given the huge amount of investment different companies have made on python for machine learning there are really nice tools available for all sort of machine learning algorithms in python. Almost every deep neural network framework is written mainly for Python or has a Python wrapper. SciPy Library provides all you need to do most of the basic machine learning algorithms work. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Unlike MATLAB different companies are developing tools for Python. There are always new libraries that are incompatible with others. I usually don't upgrade to a new version of a library until I something stops working. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

If you are familiar with basic of OO programming. Using Python machine-learning tools should be easy for you. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

We train different machine learning algorithm for computer vision applications. Review collected by and hosted on G2.com.

Verified User in Higher Education
GH
Enterprise(> 1000 emp.)
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What do you like best about machine-learning in Python?

scikit-learn package included with most of efficient and recent machine learning tools such as Random Forest, SVM, Boosting and so on. Its really easy and fast with python scikit-learn package. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

You just need basic coding skills in python. Once you are familiar with python coding which is pretty easy, machine learning applications are piece of cake using python. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

I have used mostly in my research work related to data mining and signal processing. Review collected by and hosted on G2.com.

Verified User in Research
GR
Small-Business(50 or fewer emp.)
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What do you like best about machine-learning in Python?

Tensor flow tool for deep learning. This is the best thing I like about python as it offers so much flexibility for deep learning Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

I find debugging a little tedious sometimes. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

Great for deep learning tools Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

Recognition problems. Python offers a bunch of libraries. Review collected by and hosted on G2.com.

Verified User in Higher Education
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Enterprise(> 1000 emp.)
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What do you like best about machine-learning in Python?

Comprehensive collections of machine learning algorithms and lots of examples and tutorials, in particular scikit-learn library have almost every possible machine learning algorithm included Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Documentation for some functions is rather limited. Not every implemented algorithm is present. Most of the additional libraries are easy to install but some can be quite cumbersome and take a while. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

Machine learning in Python have lots of great libraries, check out tutorials for each module before using it as it usually has lots of useful examples. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

Unsupervised clustering and classification. The most popular library scikit-learn (or sklearn) have a collection of examples and tutorials that can be easily followed. Other modules are easy to install. Review collected by and hosted on G2.com.

Verified User in Telecommunications
GT
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What do you like best about machine-learning in Python?

Ease of Setup, plethora of options, tutorials, blogs, resources available, Ease of start Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Nothing. It is great. Because everything is open source, finding support or help can be a bit tricky for custom problems. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

There are great courses available online. Pick one. Get started. Buy some cloud space if you don't have processing power, find a project on Kaggle and just get started Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

Multiple things. Trying sentiment detection, voice profiling, NLP on phonecalls Review collected by and hosted on G2.com.

Verified User in Computer Software
GC
Enterprise(> 1000 emp.)
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What do you like best about machine-learning in Python?

The ease of implementation that python libraries offer and available documentation. Review collected by and hosted on G2.com.

What do you dislike about machine-learning in Python?

Too many ways to implement the same thing, sometimes ot becomes confusing. Review collected by and hosted on G2.com.

Recommendations to others considering machine-learning in Python:

Start with the basic iris dataset classification problem. Review collected by and hosted on G2.com.

What problems is machine-learning in Python solving and how is that benefiting you?

I solve a lot of classification and regression problems with scikit learn library. A well explained documentation is available online. There are many websites for beginners. With just a few lines of code you can train your own Machine learning model. Review collected by and hosted on G2.com.