Vector Datasets (VDF)
Collection
7 items • Updated
id int64 5k 5.98k | vector sequence | title stringlengths 1 168 | link stringlengths 37 142 | reading_time int64 1 67 | publication stringclasses 6
values | claps int64 0 14.8k | responses int64 0 73 | vector_text-embedding-3-small dict |
|---|---|---|---|---|---|---|---|---|
5,000 | [
-0.019721975550055504,
-0.008513241074979305,
0.025897398591041565,
0.007900750264525414,
-0.01878613419830799,
-0.046292293816804886,
0.016931479796767235,
-0.012850852683186531,
0.032373759895563126,
-0.04266525059938431,
0.0026883480604737997,
0.04132046550512314,
0.009402637369930744,
... | A Beginner’s Introduction To TensorFlow Lite | https://towardsdatascience.com/a-beginners-introduction-to-tensorflow-lite-924320deed5 | 5 | Towards Data Science | 163 | 0 | {
"embedding": [
-0.009438722394406796,
-0.053235094994306564,
0.003700772998854518,
-0.05617703124880791,
0.009771441109478474,
-0.06075338274240494,
-0.004564675968140364,
0.04139728844165802,
0.002971125300973654,
0.01909925788640976,
0.006590177770704031,
0.01124824... |
5,001 | [
-0.04547145962715149,
-0.022726966068148613,
-0.019883399829268456,
0.0025534164160490036,
-0.017978662624955177,
0.04287497699260712,
0.001977433217689395,
0.006926830392330885,
-0.011658931151032448,
-0.032166775315999985,
-0.032467424869537354,
0.04606087878346443,
-0.029249895364046097,
... | Natural Language Processing with PySpark and Spark-NLP | https://towardsdatascience.com/natural-language-processing-with-pyspark-and-spark-nlp-b5b29f8faba | 6 | Towards Data Science | 68 | 2 | {
"embedding": [
-0.002827155403792858,
-0.01606559567153454,
0.01264922320842743,
-0.04865086078643799,
0.01632506586611271,
-0.015341237187385559,
-0.006719224154949188,
0.04657508805394173,
-0.01296275109052658,
0.0231794323772192,
-0.001990630989894271,
-0.020714454... |
5,002 | [
0.014059856534004211,
0.015085904859006405,
-0.009074200876057148,
0.02860819175839424,
0.007807536516338587,
0.0025784641038626432,
-0.011429415084421635,
-0.011282293125987053,
-0.030551865696907043,
-0.0690617486834526,
-0.03237262740731239,
0.05527113750576973,
-0.012402771972119808,
-... | Image Processing Techniques for Computer Vision | https://towardsdatascience.com/image-processing-techniques-for-computer-vision-11f92f511e21 | 3 | Towards Data Science | 286 | 0 | {
"embedding": [
-0.05792718753218651,
0.01681891642510891,
-0.006844422779977322,
-0.014043586328625679,
-0.004773358814418316,
-0.03388823941349983,
0.04008578136563301,
0.03345002979040146,
-0.040816131979227066,
0.06777647882699966,
0.03885461762547493,
-0.010517039... |
5,003 | [-0.011688449420034885,0.0036765760742127895,-0.012500499375164509,-0.008122476749122143,-0.03595436(...TRUNCATED) | Object Detection with Haar Cascades in Python | https://towardsdatascience.com/object-detection-with-haar-cascades-in-python-ad9e70ed50aa | 7 | Towards Data Science | 20 | 2 | {"embedding":[-0.012947854585945606,-0.02189144492149353,0.015687035396695137,-0.004826568532735109,(...TRUNCATED) |
5,004 | [0.008298886939883232,0.007425108924508095,0.022841716185212135,0.003498183097690344,0.0081406626850(...TRUNCATED) | Boosting Techniques in Python: Predicting Hotel Cancellations | "https://towardsdatascience.com/boosting-techniques-in-python-predicting-hotel-cancellations-62b7a76(...TRUNCATED) | 7 | Towards Data Science | 57 | 0 | {"embedding":[-0.03864070028066635,-0.014417579397559166,0.010307710617780685,-0.0065810768865048885(...TRUNCATED) |
5,005 | [-0.012367372401058674,0.024391159415245056,0.012134413234889507,0.01719384826719761,0.0135723790153(...TRUNCATED) | 3 Key Takeaways from a Machine Learning Course | https://towardsdatascience.com/3-key-takeaways-from-a-machine-learning-course-4a36030960d5 | 3 | Towards Data Science | 136 | 0 | {"embedding":[-0.03444478660821915,0.001647159457206726,0.0338318906724453,-0.044251132756471634,0.0(...TRUNCATED) |
5,006 | [0.07240444421768188,-0.020619092509150505,0.004006907343864441,0.0390702523291111,-0.00203425367362(...TRUNCATED) | Share your Projects even more easily with this New Streamlit Feature | "https://towardsdatascience.com/share-your-projects-even-more-easily-with-this-new-streamlit-feature(...TRUNCATED) | 5 | Towards Data Science | 674 | 1 | {"embedding":[0.01880607195198536,-0.051769521087408066,-0.017802376300096512,-0.008914395235478878,(...TRUNCATED) |
5,007 | [0.03474083170294762,0.03579360991716385,-0.0066583603620529175,0.007443467155098915,0.0160925090312(...TRUNCATED) | How I built a Hacker News clone for Coronavirus in less than a day | "https://towardsdatascience.com/how-i-built-a-hacker-news-clone-for-coronavirus-in-less-than-a-day-f(...TRUNCATED) | 4 | Towards Data Science | 74 | 0 | {"embedding":[-0.04174540191888809,-0.02394751086831093,-0.013774320483207703,0.024861643090844154,0(...TRUNCATED) |
5,008 | [0.032738860696554184,0.002409045584499836,-0.000672285386826843,0.02925727143883705,0.0031925272196(...TRUNCATED) | What’s your Data Science personality type? | https://towardsdatascience.com/whats-your-data-science-personality-type-a8ff7110b664 | 7 | Towards Data Science | 130 | 2 | {"embedding":[0.00012193094880785793,-0.008659375831484795,-0.0012052443344146013,-0.016380546614527(...TRUNCATED) |
5,009 | [0.03541962057352066,0.008320026099681854,0.012001678347587585,0.042393021285533905,0.01995848305523(...TRUNCATED) | The Development and Trend of Big Data and Its Applications | "https://towardsdatascience.com/the-development-and-trend-of-big-data-and-its-applications-5dd8c52e1(...TRUNCATED) | 9 | Towards Data Science | 22 | 1 | {"embedding":[0.03152039647102356,-0.029899809509515762,0.05724719539284706,0.0012034116080030799,0.(...TRUNCATED) |
End of preview. Expand in Data Studio
This is a dataset created using vector-io
- Downloads last month
- 9