Sun.Feb 18, 2024

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Deploying Models with Xinference

Towards AI

Below is a comparison of Xinference with other model deployment and inference tools: Xinference supports two installation methods: Docker image and local installation. For those interested in the Docker method, please refer to the official Docker Installation Documentation. Here, we will focus on local installation.

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Performing Data Science Tasks with LLM-Based Agents CrewAI

Towards AI

The first thing we need to do is to install the CrewAI. pip install crewai Then, let’s try out the CrewAI agents for our work. I want to experiment with whether CrewAI could perform data science tasks or not. So, let’s get into it. You can do that by executing the following code in your CLI.

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EarlyStopping and LiveLossPlot Callbacks in TensorFlow, Keras, and Python

Towards AI

First, I needed to install livelossplot by running the following line: !pip… It keeps plotting the loss and evaluation metric as the model trains. It is very cool. I used a Google Colab notebook for this exercise. You can use any other platform of your choice. pip… Read the full blog for free on Medium.

Python 89
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Causal Inference Python Implementation

Towards AI

pip install pycausalimpactfrom causalimpact import CausalImpact Loading the dataset Once the libraries have been imported, it’s time to import the dataset to be used.

Python 103