1/ "Software is eating the world. Machine learning is eating software. Transformers are eating machine learning."

Let's understand what these Transformers are all about

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataAnalytics 2/ #Transformers architecture follows Encoder and Decoder structure.

The encoder receives input sequence and creates intermediate representation by applying embedding and attention mechanism.

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But what p-value means in #MachineLearning - A thread

It tells you how likely it is that your data could have occurred under the null hypothesis

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What Is a Null Hypothesis?

A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.

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1/ One way to test whether a time series is stationary is to perform an augmented Dickey-Fuller test - A Thread

#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics #programming #ArtificialIntelligence 2/ H0: The time series is non-stationary. In other words, it has some time-dependent structure and does not have constant variance over time.

HA: The time series is stationary.

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Kullback-Leibler (KL) Divergence - A Thread

It is a measure of how one probability distribution diverges from another expected probability distribution.

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1/ When it is important to standardize variables in #DataScience #MachineLearning ? - A Thread

#DeepLearning #100DaysOfMLCode #Python #pythoncode #AI #DataScientist #DataAnalytics #Statistics #programming #ArtificialIntelligence #Data #Stats #Database #BigData #100DaysOfCode 2/ It is important to standardize variables before running Cluster Analysis. It is because cluster analysis techniques depend on the concept of measuring the distance between the different observations we're trying to cluster.

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Did you know how TensorFlow can run on a single mobile device as well as on an entire data center? Read this thread

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Google has designed TensorFlow such that it is capable of dividing a large model graph whenever needed.

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A thread on AUC Score (Area under the ROC Curve) Interpretation in #DataScience #MachineLearning

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"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.

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Outlier Detection with Alibi Detect Library - A Thread
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Alibi Detect is a Python library for detecting outliers, adversarial data, and drift. Accommodates tabular data, text, images, and time series that can be used both online and offline. Both TensorFlow and PyTorch backends are supported

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1/ Can you classify something without seeing it before - that's what Zero-Shot Learning is all about - A Thread

👉 One of the popular methods for zero-shot learning is Natural Language Inference (NLI).

#DataScience #DeepLearning #MachineLearning #100DaysOfMLCode #Pytho 2/ Zero-shot learning is when we test a model on a task for which it hasn't been trained.

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1/ Why do we need the bias term in ML algorithms such as linear regression and neural networks ? - A thread

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats #DeepLearning #100DaysOfCode 2/ In linear regression, without the bias term your solution has to go through the origin. That is, when all of your features are zero, your predicted value would also have to be zero.

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Google has released Imagen: a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding

#Python3 #MachineLearning #DataScience #100DaysOfCode #DataScience #DataAnalytics #100DaysOfMLCode #DataScientist #Statistics Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation.

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What is p-value - A thread

It tells you how likely it is that your data could have occurred under the null hypothesis.

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#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat 2/n
What Is a Null Hypothesis?

A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.

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1/ #MachineLearning #Interview questsion -
Why L1 regularizations causes parameter sparsity whereas L2 regularization does not?

#DataScience #MachineLearning #100DaysOfMLCode #DataScientist #Statistics #programming #ArtificialIntelligence #Data #pythoncode #AI #Stats 2/ L1 & L2 regularization add constraints to the optimization problem. The curve H0 is the hypothesis. The solution to this system is the set of points where the H0 meets the constraints.

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A thread on AUC Score (Area under the ROC Curve) Interpretation in #DataScience #MachineLearning

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"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.

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Some tips to increase the Performance of Your Object Detection Models - A trhead
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Following tips may boost model performance across different network structures with up to 5% (mAP or mean Average Precision) without increasing computational costs in any way.

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