Amanmehta-maniac.github.io receives about 244 visitors in one month. That could possibly earn $1.22 each month or $0.04 each day. Server of the website is located in the United States. Amanmehta-maniac.github.io main page was reached and loaded in 0.32 seconds. This is a good result. Try the services listed at the bottom of the page to search for available improvements.
Traffic and Value
| Is amanmehta-maniac.github.io legit? | |
| Website Value | $22 |
| Alexa Rank | 14727754 |
| Monthly Visits | 244 |
| Daily Visits | 9 |
| Monthly Earnings | $1.22 |
| Daily Earnings | $0.04 |
Amanmehta-maniac.github.io Server Location
Country: United States
Metropolitan Area: Not defined
Postal Reference Code: Not defined
Latitude: 37.751
Longitude: -97.822
Summarized Content
Amanmehta-maniac Main Page Content
| HTML Tag | Content | Informative? |
|---|---|---|
| Title: | Aman's GSoC | Could be improved |
| Description: | DBpedia GSoC’18 - A Neural QA | Could be improved |
| H2: | Final Week: Coding Period 8 (7th Aug - 14th Aug) | Is it informative enough? |
| H3: | Aman Mehta | Is it informative enough? |
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Internal Pages
| /page2/: | |
|---|---|
| Title |
Aman's GSoC Journey - Page 2 |
| Description |
DBpedia GSoC’18 - A Neural QA model |
| H2 |
Coding Period 3 (28th May - 11th June) |
| H3 |
Aman Mehta |
| /Coding-Period-8/: | |
|---|---|
| Title |
Final Week: Coding Period 8 (7th Aug - 14th Aug) - Aman’s GSoC Journey |
| Description |
After completing the required scripts to fetch all the templates and testing their correctness, I was ready to generate the train and test data for the composition idea. |
| H1 |
Final Week: Coding Period 8 (7th Aug - 14th Aug) |
| H2 |
Coding Period 7 (24th July - 6th Aug) |
| H3 |
Aman Mehta |
| /Coding-Period-7/: | |
|---|---|
| Title |
Coding Period 7 (24th July - 6th Aug) - Aman’s GSoC Journey |
| Description |
In continuation with the problems with the version-1 of our model (which was getting 11% BLEU accuracy), I discussed the output with mentors. After a day or two of error ysis, we realised that there were few trivial problems with our dataset, due to which our BLEU score was so low: [censored]
|
| H1 |
Coding Period 7 (24th July - 6th Aug) |
| H2 |
Final Week: Coding Period 8 (7th Aug - 14th Aug) |
| H3 |
Aman Mehta |
| /Coding-Period-6/: | |
|---|---|
| Title |
Coding Period 6 (10th July - 23rd July) - Aman’s GSoC Journey |
| Description |
During the initial stages of this duration, I completed final formatting steps to get the templates ready. In a few days, the training templates were ready to generate dataset! I began with generation of the dataset and finished it in a day, there were a couple of proxy issues which caught up my entire day. There is a hyper-parameter to create a dataset: EXAMPLES_PER_TEMPLATE (let’s call it ex for ease), which as the name suggests, uses SPARQL endpoint to get that many number of pairs in the dataset. For starters, (just to check if the data-generation process is flawless) I took ex = 1. |
| H1 |
Coding Period 6 (10th July - 23rd July) |
| H2 |
Final Week: Coding Period 8 (7th Aug - 14th Aug) |
| H3 |
Aman Mehta |
| /Coding-Period-5/: | |
|---|---|
| Title |
Coding Period 5 (26th June - 9th July) - Aman’s GSoC Journey |
| Description |
Keeping in mind our ultimate goal of this project - We want to automatically generate training data using a single command or a sinlge script, it is important to devise another script which will automatically perform all the sub-tasks. In the current scenario, there are different scripts which perform a sub-task each in a serial fashion to five us the required training set. To club this in a single script, it is important to address each of the subtask and reduce the hard-coded portions and properly define all the parameters. |
| H1 |
Coding Period 5 (26th June - 9th July) |
| H2 |
Final Week: Coding Period 8 (7th Aug - 14th Aug) |
| H3 |
Aman Mehta |
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