ProxyCompass
Google CLOUD AUTOML
Qubole
BigML
TensorFlow
Scikit-learn
AWS SageMaker Ground Truth
RapidMiner
MATLAB
machine-learning in Python
Scikit-learn
BigML
Google Cloud TPU
Amazon Forecast
AWS Personalize
python-recsys
Qubole
Google CLOUD AUTOMLmachine-learning in Python might be a bit more popular than Google CLOUD AUTOML. We know about 7 links to it since March 2021 and only 6 links to Google CLOUD AUTOML. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are several no-code AI websites that you can use like Amazon SageMaker, Apple CreateML or Google AutoML. Source: about 1 year ago
GCP, on the other hand, offers two top options: Google Cloud AutoML, for beginners, and Google Cloud Machine Learning Engine, for handling tasking projects. GCP also provides Tenserflow and Vertex AI complicated machine learning abilities. - Source: dev.to / over 1 year ago
Just outsource the work to Google or Amazon. Source: over 2 years ago
We can also note the appearance of Machine Learning, creating dynamic processes over data that would have been tedious to analyse, either by hand or through specific code. This enables writing potentially complex behaviours with a few lines of code in some cases. Even then, there is some automation of it to the point where you only have to provide data to get working results. - Source: dev.to / almost 3 years ago
You might want to check out automl Google AutoML. Source: almost 3 years ago
After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: about 1 year ago
Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / over 1 year ago
MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: about 2 years ago
Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.
Amazon Forecast - Accurate time-series forecasting service, based on the same technology used at Amazon.com. No machine learning experience required.