AI model development: Stages and the best datacenter proxies’ role

Contents of article:

  1. AI life cycle from a trusted proxy website’s view
  2. How to train an AI model: buy Dexodata’s residential rotating proxies

Artificial intelligence automates recurring tasks and advances informed predictions, that is why most companies (54%) use generative AI for everyday tasks. Specifics of various business processes require adaptation of existing or creation of new AI-based models by analogy with choosing services from trusted proxy websites. While the Dexodata ecosystem offers the best datacenter proxies, residential, and 3G/4G/LTE IP addresses, the choice of particular pools’ type and geolocation depends on the projects.

Dynamic IP rotation, API-engaged management, city and ISP-level targeting make our innovative proxy service a reliable tool for scaled web data harvesting, including cases of AI models development and training. What stages are there, and which of them require buying residential rotating proxies, is explained below.

AI life cycle from a trusted proxy website’s view

AI life cycle includes phases of creating and leveraging algorithms applying machine learning, from defining problems requiring AI implementation to the finished ML-enabled framework’s operation and maintenance. A trusted proxy website’s utilization is typical for stages related to collecting publicly available information:

  1. Creating training datasets
  2. Improving them for higher accuracy and relevance
  3. Using developed digital robots as intended, e.g. for AI-enhanced web data gathering.

Stages of AI model creation are in our spotlight:

Stage Description Techniques and features
Data acquisition Gathering and preparing information suitable for the task from online and internal sources
  • Web scraping
  • API calls
  • Queries to databases
  • File imports. 

Performers buy residential rotating proxies or other IPs to perform HTTP requests seamlessly

Preparation Cleaning and converting raw information into a format suitable for analysis The variables obtained pass cleaning, normalization, encoding. Data enrichment assists finding and recovering missing values, error correction, etc.
Featurization Raising the AI-oriented model’s performance through adding required features or adjusting the available ones, for example an ability to operate the best datacenter proxies during the procedure Features’ generation, aggregation, scaling along with handling parameters’ outliers and reducing dimensionality
Splitting the info Defining the collected information as datasets for future training, validation, and testing

Splitting:

  • Random
  • Stratified
  • Time-based
Selecting the model Considering the most appropriate AI’s architecture as the primary algorithm

Comparative analysis, cross-validation, ensemble methods, etc. The main tools are:

  • Scikit-learn
  • TensorFlow (Keras Tuner)
  • Optuna
  • PyTorch
  • MLflow
  • Hyperopt
Training Feeding the chosen ML-enabled model with prepared insights
  • Gradient descent
  • Backpropagation
  • Regularization
Hyperparameters’ setup Optimizing model parameters to improve performance

ML frameworks’ accuracy raising methods:

  • Fine-tuning
  • Strategic L1 and L2 regularization
  • Cross-validation

Refining data quality through additional data harvesting with a trusted proxy website

Benchmarking Evaluating the efficacy of a machine learning technology via diverse performance indicators Confusion matrix, ROC curve, train-test split, mean squared error, and more
Validation Checking the AI’s reliability on new, previously unused insights

A/B testing, validation techniques, such as:

  • Cross
  • Holdout
  • Continuous
Deployment Making the model available for work with the set production environments API development, containerization, cloud or on-premises infrastructure

 

How to train an AI model: buy Dexodata’s residential rotating proxies

 

Accessing the sources of publicly available online information strives for buying residential rotating proxies. Dexodata provides:

  1. KYC and AML policies’ strict compliance
  2. 100+ countries to choose from 
  3. Rotating IPs capable of processing HTTP(S) and SOCKS5
  4. VPN-ready ports with TLS encryption.

These features are essential during ingesting and preprocessing training datasets, engineering features, and deploying the ready-made ML technology. You can perform the extraction of internet info through AI-based models for raised accuracy and velocity. Sign up for a free proxy trial, and test the best Dexodata’s datacenter proxies, residential or mobile addresses in action.

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