How to Measure Keyword Difficulty and Rank on Google

Learn a data-driven keyword research process to measure keyword difficulty. These tips will help you choose keywords that you can ACTUALLY rank for on Google.

In this video, you’ll learn 3 different ways to gauge keyword difficulty as well as an advanced keyword research tactic that most people aren’t doing.

More specifically, here’s what you’ll learn:

- How to analyze the top 10 ranking results and why it's more accurate than Keyword Difficulty scores.
- What the most important metrics are when determining keyword difficulty.
- How to include a 1-minute backlink analysis into your process.
- The power of matching the searcher’s intent.
- Bonus: How to analyze SERP volatility.

By using this proven analysis, you’ll be able to choose the right keywords to target instead of wasting your time chasing after arbitrary search volume numbers.

Timestamps:

0:50 Analyze the top 10 ranking results to get a more accurate score
2:17 Check if the results are matching searcher’s intent
3:51 Include a backlink analysis in KD research process
5:56 Analyze SERP volatility for more refined results

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How to Measure Keyword Difficulty and Rank on Google

Machine Learning in Rust

1619247660

Google's TPU's being primed for the Quantum Jump

The liquid-cooled Tensor Processing Units, built to slot into server racks, can deliver up to 100 petaflops of compute.

As the world is gearing towards more automation and AI, the need for quantum computing has also grown exponentially. Quantum computing lies at the intersection of quantum physics and high-end computer technology, and in more than one way, hold the key to our AI-driven future.

Quantum computing requires state-of-the-art tools to perform high-end computing. This is where TPUs come in handy. TPUs or Tensor Processing Units are custom-built ASICs (Application Specific Integrated Circuits) to execute machine learning tasks efficiently. TPUs are specific hardware developed by Google for neural network machine learning, specially customised to Google’s Machine Learning software, Tensorflow.

The liquid-cooled Tensor Processing units, built to slot into server racks, can deliver up to 100 petaflops of compute. It powers Google products like Google Search, Gmail, Google Photos and Google Cloud AI APIs.

#opinions #alphabet #asics #floq #google #google alphabet #google quantum computing #google tensorflow #google tensorflow quantum #google tpu #google tpus #machine learning #quantum computer #quantum computing #quantum computing programming #quantum leap #sandbox #secret development #tensorflow #tpu #tpus

Md Delwar Husain

1598383290

What Are Google Compute Engine ? - Explained

The Google computer engine exchanges a large number of scalable virtual machines to serve as clusters used for that purpose. GCE can be managed through a RESTful API, command line interface, or web console. The computing engine is serviced for a minimum of 10-minutes per use. There is no up or front fee or time commitment. GCE competes with Amazon’s Elastic Compute Cloud (EC2) and Microsoft Azure.

https://www.mrdeluofficial.com/2020/08/what-are-google-compute-engine-explained.html

#google compute engine #google compute engine tutorial #google app engine #google cloud console #google cloud storage #google compute engine documentation

Mable Wilderman

1596830700

Embedding your <image> in google colab <markdown>

This article is a quick guide to help you embed images in google colab markdown without mounting your google drive!

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Just a quick intro to google colab

Google colab is a cloud service that offers FREE python notebook environments to developers and learners, along with FREE GPU and TPU. Users can write and execute Python code in the browser itself without any pre-configuration. It offers two types of cells: text and code. The ‘code’ cells act like code editor, coding and execution in done this block. The ‘text’ cells are used to embed textual description/explanation along with code, it is formatted using a simple markup language called ‘markdown’.

Embedding Images in markdown

If you are a regular colab user, like me, using markdown to add additional details to your code will be your habit too! While working on colab, I tried to embed images along with text in markdown, but it took me almost an hour to figure out the way to do it. So here is an easy guide that will help you.

STEP 1:

The first step is to get the image into your google drive. So upload all the images you want to embed in markdown in your google drive.

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Step 2:

Google Drive gives you the option to share the image via a sharable link. Right-click your image and you will find an option to get a sharable link.

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On selecting ‘Get shareable link’, Google will create and display sharable link for the particular image.

#google-cloud-platform #google-collaboratory #google-colaboratory #google-cloud #google-colab #cloud

Jack Wood

1637277420