Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
AI & Analytics Engine
cnvrg CORE
datarobot
Azure Machine Learning Studio
H2O.ai
ML Dictionary
Dataiku DSS
Amazon Machine Learning
The PI.EXCHANGE AI & Analytics Engine (the Engine) is a Data Science and Machine Learning (ML) platform that empowers everyone, even novice users, to affordably build high-performance ML applications in minutes or hours, not weeks or months.
The easy-to-use connected toolchain provides everything you will need to go from raw data to predictions and insights within a single pipeline. Manual and repetitive machine learning tasks are automated, and the Engine's intelligent features help guide the user end-to-end. So, whether you are building a small pilot project with no dedicated data science resources, or are deploying large-scale enterprise ML systems, you can equip your existing team with the right tool to build meaningful solutions, fast. The Engine gives users the flexibility to customize their ML pipeline from scratch for classification, regression, time-series, or clustering problems or to select an ML solution template to develop their ML application. While both ML development options are guided and require no-coding experience, the latter requires only articulation of business requirements and problem context via a few key steps - everything else is taken care of.
Notable AI solutions include: Customer Churn Prediction Leveraging your manufacturing data to build predictive maintenance strategies Predict online fraudulent transactions and reduce false positives and; Optimize logistics decision-making
Pandas AI & Analytics EngineBased on our record, Pandas seems to be a lot more popular than AI & Analytics Engine. While we know about 219 links to Pandas, we've tracked only 1 mention of AI & Analytics Engine. 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.
Libraries for data science and deep learning that are always changing. - Source: dev.to / 17 days ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 1 month ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 1 month ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 3 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
DISCLAIMER: Hello everyone, my name is Fyona & I work in Marketing at PI.EXCHANGE. I wanted to share an EXCITING news regarding our upcoming release that I think can be helpful to many! The AI & Analytics Engine will be offering a Machine Learning (ML) Solution Templates, starting with our Customer Churn Prediction Template. Source: about 2 years ago
NumPy - NumPy is the fundamental package for scientific computing with Python
cnvrg CORE - Free ML Platform for everyone
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
datarobot - Become an AI-Driven Enterprise with Automated Machine Learning
OpenCV - OpenCV is the world's biggest computer vision library
Azure Machine Learning Studio - Azure Machine Learning Studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure.
