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Details: MLK is a knowledge sharing community platform for machine learning enthusiasts, beginners & experts. Let us create a powerful hub together to Make AI Simple

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Build a Machine Learning Web App with Streamlit and Python

Details: Due to its ease of use, in this tutorial, we will build machine learning web application with Streamlit. What is Heroku . Heroku is a cloud platform as a service (PaaS) where you can host your applications written in various languages like Java, Python, Scala, Node.js, etc. Once hosted, the application can be accessed on the internet by using their domain name in their free plan.

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PyTorch Tensor - Explained for Beginners | MLK - Machine

Details: In this tutorial, we'll learn about the PyTorch tensor along with various exampes and operations for easy explaination for beginners.

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Different Types of Keras Layers Explained for Beginners

Details: Introduction. Keras layers are the building blocks of the Keras library that can be stacked together just like legos for creating neural network models. This ease of creating neural networks is what makes Keras the preferred deep learning framework by many. There are different types of Keras layers available for different purposes while designing your neural network architecture.

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Why and How to do Feature Scaling in Machine Learning

Details: Introduction. Feature scaling in machine learning is one of the most important steps during the preprocessing of data before creating a machine learning model. This can make a difference between a weak machine learning model and a strong one. Before we jump on to various techniques of feature scaling let us take some effort to understand why we need feature scaling, only then we would be able

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Overfitting and Underfitting in Machine Learning

Details: Introduction. Overfitting and underfitting in machine learning are phenomena that result in a very poor model during the training phase. These are the types of models you should avoid creating during training as they can’t be used in production and are nothing more than a piece for trash.

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OpenCV Tutorial - Image Colorspace Conversion using cv2

Details: src: It is the image whose color space is to be changed.. code: It is the color space conversion code.It is basically an integer code representing the type of the conversion, for example, RGB to Grayscale. Some codes are. cv2.COLOR_BGR2GRAY: This code is used to convert BGR colored image to grayscale. cv2.COLOR_BGR2HSV: This code is used to change the BGR color space to HSV color space.

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14 Computer Vision Applications Beginners Should Know

Details: The objective of object classification is to assign a label to an input image from a fixed set of categories or class.For humans, this task is effortless but for computers to classify an image is not a straightforward task. Yet the modern computer vision techniques are able to classify images with great accuracy.

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21 OpenAI GPT-3 Demos and Examples to Convince You that AI

Details: With all the hype around GPT-3 results being circulated online, people have been apprehensive about these advanced language models. The previous version GPT-2 was already considered so advanced with its results that the AI community was worried about its potential threats.This same fear is attached to GPT-3 with increased powers.

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What is Predictive Power Score (PPS) - Is it better than

Details: Introduction. Every time when we try to solve a data science problem, our aim is to extract as much insight as possible from the data. This also involves deriving the relationship between two different attributes or features of a dataset and traditionally Correlation Matrix is widely used for this purpose.

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Autoencoders in Keras - Introduction to Beginners with

Details: In this tutorial, we will show how to build Autoencoders in Keras for beginners along with example for easy understanding.

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Keras Tokenizer Tutorial with Examples for Beginners | MLK

Details: In this article, we will go through the tutorial of Keras Tokenizer API for dealing with natural language processing (NLP). We will first understand the concept of tokenization in NLP and see different types of Keras tokenizer functions – fit_on_texts, texts_to_sequences, texts_to_matrix, sequences_to_matrix with examples.

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Tutorial - How to use Spotipy API to scrape Spotify Data

Details: Introduction. In this article, we will learn how to scrape data from Spotify which is a popular music streaming and podcast platform. This scraping will be done by using a Web API of Spotify, known as Spotipy.Our aim through this hands-on experience of web scraping is to fetch the information of all the tracks in Spotify playlists.We can obtain the information of tracks of any playlist, we

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Pandas Tutorial - groupby(), where() and filter() | MLK

Details: Pandas Where: where() The pandas where function is used to replace the values where the conditions are not fulfilled.. Syntax. pandas.DataFrame.where(cond, other=nan, inplace=False, axis=None, level=None, try_cast=False) cond : bool Series/DataFrame, array-like, or callable – This is the condition used to check for executing the operations.. other : scalar, Series/DataFrame, or callable

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Seaborn Countplot using sns.countplot() - Tutorial for

Details: In this article, we will go through seaborn countplot using sns.countplot() function along with syntaxes and various examples for beginners.

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Dummies guide to Cost Functions in Machine Learning [with

Details: Cost functions in machine learning are used to calculate deviation between predicted output and actual output during training phase of a model.

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How to deal with Missing Data in Machine Learning | MLK

Details: Introduction. As a machine learning practitioner or data scientist you would like to work on a data set that does not contain any missing data or values. But unfortunately a perfect world does not exist and neither does a perfect data set. It is very regular to come across data sets where some data is missing.

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11 Interesting Natural Language Processing GitHub Projects

Details: DeepMoji is a deep learning model that can be used for analyzing sentiment, emotion, sarcasm, etc. DeepMoji is a model trained on 1.2 billion tweets with emojis to draw inferences of how language is used to express emotions. The repository contains the deep learning model along with examples of code snippets, data for training, and tests for evaluating the code.

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Seaborn Bar Plot with sns.barplot() - Examples for

Details: In this variable, we provide the inputs to the function. data: DataFrame, array, or list of arrays, optional. Here the dataset or dataframe for plotting bar plot is passed. order, hue_order: lists of strings, optional. This is the order for plotting categorical variables.

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Keras Convolution Layer - A Beginner's Guide | MLK

Details: Results. The final results show that the accuracy achieved by the model is around 98.75%.. The graphs of Cross-Entropy Loss and Classification Accuracy show that in the training set (depicted by the blue line) loss is almost 0% and accuracy is nearer to 100% whereas in the case of the testing set (depicted by the orange line) loss is nearer to 0.1% and accuracy is 98.75%.

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9 Machine Learning Projects in Python with Code in GitHub

Details: Introduction. Deep Learning has been the most revolutionary branch of machine learning in recent years due to its amazing results. In this article, we will let you know some interesting machine learning projects in python with code in Github. You can either fork these projects and make improvements to it or you can take inspiration to develop your own deep learning projects from scratch.

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Seaborn Histogram Plot using histplot() - Tutorial for

Details: data : pandas.DataFrame, numpy.ndarray, mapping, or sequence – Here we provide the input data for the visualization; x, y : vectors or keys in data – Through this parameter, we mention the x and y axes positions.; hue : vector or key in data – This parameter helps in mapping of variables to color for plot.; weights : vector or key in data – Weights help in understanding the impact of

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Tutorial - numpy.arange() , numpy.linspace() , numpy

Details: While working with machine learning or data science projects, you might be often be required to generate a numpy array with a sequence of numbers. In this post we will see how numpy.arange(), numpy.linspace() and numpy.logspace() can be used to create such sequences of array.

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Tutorial - Numpy Mean, Numpy Median, Numpy Mode, Numpy

Details: Commencing this tutorial with the mean function.. Numpy Mean : np.mean() The numpy mean function is used for computing the arithmetic mean of the input values.Arithmetic mean is the sum of the elements along the axis divided by the number of elements.. We will now look at the syntax of numpy.mean() or np.mean().

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Matplotlib Scatter Plot - Complete Tutorial for Beginners

Details: x,y: Float or array-like, shape(n,) – These are the two sets of values provided to the scatter function for plotting.; s: Float or array-like, shape(n,) – This parameter specifies the size of the marker; c: Array-like or List of Color or Color – This specifies the color of the marker; marker: MarkerStyle – For setting the marker style, this parameter comes handy

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Matplotlib Surface Plot - Tutorial for Beginners | MLK

Details: Example 1 : Simple Matplotlib Surface Plot in 3D. The first example of surface plot shows how a simple 3D surface plot can be built. Initially, data is generated with the help of arange function. The data is arranged over a meshgrid and then plot_surface is called for plotting a surface plot.. In this function, the data for three dimensions is provided which helps in plotting.

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[Animation] Gentle Introduction to Ensemble Learning for

Details: Ensemble Learning is a powerful technique of combining multiple machine learning models to create a more powerful model having low variance and low bias.

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Microsoft Hummingbird Library - Converts your Traditional

Details: Microsoft Hummingbird is an open-source library that can be used for converting already trained traditional ML Models (that are not neural networks) into tensor-based computational models.

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Neural Network Primitives Part 1 - McCulloch Pitts Neuron

Details: Introduction. Modern machine learning world is going crazy over deep learning.People are stacking hundreds and thousands of interconnected artificial neurons to build the most complex of deep neural network than ever. These deep neural nets are able to create the most astonishing AIs that are outperforming humans in many tasks.

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Matplotlib Heatmap - Complete Tutorial for Beginners | MLK

Details: Matplotlib Heatmap Tutorial. Heatmap is an interesting visualization that helps in knowing the data intensity.It conveys this information by using different colors and gradients. Heatmap is also used in finding the correlation between different sets of attributes.. NOTE – There isn’t any dedicated function in Matplotlib for building Heatmaps. This is why majorly imshow function is used.

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Python OpenCV - Image Smoothing using Averaging, Gaussian

Details: ksize: A tuple representing the blurring kernel size. dst: It is the output image of the same size and type as src. anchor: It is a variable of type integer representing anchor point and it’s default value Point is (-1, -1) which means that the anchor is at the kernel center. borderType: It depicts what kind of border to be added. It is defined by flags like cv2.BORDER_CONSTANT, cv2.BORDER

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PyTorch Stack vs Cat Explained for Beginners | MLK

Details: In this tutorial, we will look at PyTorch Stack and Cat functions that are used for joining tensors along with comparison of stack vs cat.

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Matplotlib Contour Plot - Tutorial for Beginners | MLK

Details: In this tutorial, we will be learning how we can build matplotlib contour plot for your data science and machine learning projects. We will go through the syntax and will see various interesting examples of contour plots that can be built using the matplotlib library.

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Matplotlib Quiver Plot - Tutorial for Beginners | MLK

Details: Example 1: Simple Matplotlib Quiver Plot. In the first example of the matplotlib quiver plot tutorial, we will create three different types of simple quiver charts.

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Seaborn Heatmap using sns.heatmap() with Examples for

Details: In this article, we’ll go tutorial of Seaborn Heatmap function sns.heatmap() that will be useful for your machine learning or data science projects. We will learn about its syntax and see various examples of creating Heatmap using the Seaborn library for easy understanding for beginners.

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Seaborn Boxplot Tutorial using sns.boxplot() - Explained

Details: In this article, we will go through the Seaborn boxplot tutorial using boxplot() function along with various examples for beginners

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7 Real Advantages of Artificial Intelligence You Should

Details: Introduction. As we are standing at the dawn of new decade of 2020, AI is the new thing that has captured the imagination of everyone. With recent advancements in big data storage and computing hardwares, decade old machine learning algorithms have come to life now and are doing wonders which can be best described as something out of the science fiction books.

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OpenCV Tutorial - Reading, Displaying and Writing Image

Details: Parameters:. path: The image should be in the working directory or a full path of image should be given.. flag: The flags option is used to control how the image is read.. cv2.IMREAD_COLOR: Loads a color image.Any transparency of the image will be neglected. It is the default flag. cv2.IMREAD_GRAYSCALE: Loads image in grayscale mode. cv2.IMREAD_UNCHANGED: This reads all of the image data

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Machine Learning Basics Archives | MLK - Machine Learning

Details: Welcome! Log into your account. your username. your password

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7 Reinforcement Learning GitHub Repositories To Give You

Details: This repository hosts the code for training and running a self-driving truck in Euro Truck Simulator 2 game. This is made achievable by the reinforcement learning-powered AI model that’s made capable to steer, accelerate, and brake the truck as per requirement. The author has taken the basic training approach from the famous Atari Paper and have added small techniques from other papers as

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Pandas Read and Write operations with CSV , JSON and Excel

Details: Next in the list is the JSON file. We will first read the data from JSON file, so let’s look at the syntax and examples of it.. Reading JSON file in Pandas : read_json() With the help of read_json function, we can convert JSON string to pandas object.. Syntax. pandas.read_json(path_or_buf=None,orient=None)

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Image Classification using Bag of Visual Words Model | MLK

Details: Clustering, which is an unsupervised learning method, is commonly used for creating visual vocabulary or codebook.; Each cluster center produced by k-means becomes a codeword. The number of clusters is the codebook size. Codebook can be learned on the separate training sets.

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Matplotlib Histogram - Complete Tutorial for Beginners

Details: Example 1: Simple Matplotlib Histogram. This is the first example of matplotlib histogram in which we generate random data by using numpy random function.. To depict the data distribution, we have passed mean and standard deviation values to variables for plotting them.

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Machine Learning Archives | Page 2 of 4 | MLK - Machine

Details: MLK is a knowledge sharing community platform for machine learning enthusiasts, beginners and experts. Let us create a powerful hub together to Make AI Simple for everyone.

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11 Best Coursera courses for Data Science and Machine

Details: Introduction. When you are trying to build a foundation in the field of Machine Learning and Data Science, one of the best approaches is to pursue some reputed courses for more robust and systematic learning.There are many online platforms that offer online courses in data science and machine learning and Coursera is one of the leaders in this online learning space.

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Beginners's Guide to Keras Models API - Sequential Model

Details: 1. Keras Sequential Model. The first way of creating neural networks is with the help of the Keras Sequential Model. The basic idea behind this API is to just arrange the Keras layers in sequential order, this is the reason why this API is called Sequential Model.Even in most of the simple artificial neural networks, layers are put in sequential order, the flow of data takes place between

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How a 3rd Year Student Brought India's First Kaggle Days

Details: MLK – So how does your community function? Ayon – We have completed 8 Kaggle meetups and the community is 1K people strong. The community thrives on helping each other on how to start machine learning & data science and how to get an internship or job.

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Learn Image Classification with Deep Neural Network using

Details: In this article, we will learn image classification with Keras using deep learning.We will not use the convolutional neural network but just a simple deep neural network which will still show very good accuracy. For this purpose, we will use the MNIST handwritten digits dataset which is often considered as the Hello World of deep learning tutorials.

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Types of Keras Loss Functions Explained for Beginners

Details: Types of Loss Functions in Keras 1. Keras Loss Function for Classification . Let us first understand the Keras loss functions for classification which is usually calculated by using probabilistic losses.

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Community Blogs Archives | MLK - Machine Learning Knowledge

Details: MLK is a knowledge sharing community platform for machine learning enthusiasts, beginners and experts. Let us create a powerful hub together to Make AI Simple for everyone.

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