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Machine Learning With Google

Learn more about computerscience with this collection

Understanding machine learning models

Improving data analysis and decision-making

How Google uses logic in machine learning

Machine Learning With Google

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Start with Datasets

Start with Datasets

Data is the new oil - and just as oil needs the right refining to come into perfect usage, data too needs curing. The power of your machine learning models will greatly depend on the quality of your data.

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Mistake - Don’t prioritize data curation

Mistake - Don’t prioritize data curation

As AI integration across industries picks greater pace, ML engineers are confronted with a sad reality - once stakeholders identify a use case with proven ROI, they are eager to jump onto the AI ship, and dat...

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Steps

  1. Formatting: The data is spread in different formats. Formatting will bring it together in one sheet. For example, customer data can come with different currencies, languages, etc. These need to be compiled under one format.
  2. Labeling: ...

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Testing Data

Testing Data

Testing data is used to test the validity of the training data set. Training data is not used for testing because it will produce the expected output. The testing data set comprises of 20 percent of the total data.

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How to start curating

The process of curating datasets for machine learning starts well before availing datasets. Here’s what we suggest:

  • Identify the goal of AI
  • Identify what dataset you will need to solve the problem
  • Make a record of your assumptions while selecting the data
  • Aim fo...

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Small Dataset = use pre-trained model

If you have a small dataset, using a model pre-trained on large datasets can be a good idea. You can use your small dataset to fine-tune it.

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Validation Data

Validation Data

Validation tests are used to identify and tune the ML model.

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Types of Datasets for Machine Learning

ML engineers depend on data during each step of their AI journey – from model selection, training, and tuning to testing. These datasets usually fall under three categories:

  1. Training sets
  2. Testing sets
  3. Validation sets

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Training Data

Training Data

The training data set is used to train an algorithm, apply concepts, learn, and give results. Around 60 percent of data is training data.

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CURATED FROM

CURATED BY

sabin

Building @deepstash

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START TODAY:

START TODAY:

Pick one thing you want to change today. It can be one attitude, one belief, or one perspective. Imagine for a moment what you want instead. Let your imagination run wild for just a moment.

Remember any resistance is just your old neural network playing up as usual. Use t...

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