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diff --git a/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html b/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html index 9d39c2b..a469dd7 100644 --- a/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html +++ b/docs/posts/2019-12-16-TensorFlow-Polynomial-Regression.html @@ -25,6 +25,8 @@ <link rel="manifest" href="manifest.json" /> <meta name="google-site-verification" content="LVeSZxz-QskhbEjHxOi7-BM5dDxTg53x2TwrjFxfL0k" /> <script async src="//gc.zgo.at/count.js" data-goatcounter="https://navanchauhan.goatcounter.com/count"></script> + <script defer data-domain="web.navan.dev" src="https://plausible.io/js/plausible.js"></script> + <script defer data-domain="web.navan.dev" src="https://plausible.navan.dev/js/plausible.js"></script> </head> <body> @@ -519,6 +521,9 @@ values using the X values. We then plot it to compare the actual data and predic <p>Basically if you train your machine learning model on a small dataset for a really large number of epochs, the model will learn all the deformities/noise in the data and will actually think that it is a normal part. Therefore when it will see some new data, it will discard that new data as noise and will impact the accuracy of the model in a negative manner</p> + <div class="commentbox"></div> + <script src="https://unpkg.com/commentbox.io/dist/commentBox.min.js"></script> + <script>commentBox('5650347917836288-proj')</script> </main> |