Pakistan Super League (PSL) Win Predictor Using Machine Learning | Streamlit | Python

Pakistan Super League (PSL) Win Predictor Using Machine Learning | Streamlit | Python | Sklearn

Video Link : https://www.youtube.com/watch?v=WsqD43zwSQ0

Other creator : Zaeem Ahmed

The growing craze for shorter formats in cricket was never at this peak before and with this growing sensation, it requires improvisation in broadcasting the cricket matches with shorter formats. Hence, we always find win predictors in the t20 matches broadcasted in 2nd innings to predict the win percentages of the respective teams, thus, to get an intuition that how it is being performed and to apply the learned machine learning techniques and those apart from the course were experimented throughout this end-to-end machine learning project. We used the dataset from Kaggle, which was ball-by-ball dataset of all the previous seasons (2016 - 2020) of Pakistan Super League (PSL). Since, we had relatively less amount of data with respect to other kernels found on Kaggle, we chose machine-learning models, which are implemented on complex datasets in order to devise a better correlation among the features being selected through our data manipulation process. In contrary to the kernels which we found during the research process, implemented linear regression and its variants (Lasso and Ridge), and logistic regression but the accuracy achieved by them was significantly lesser than we achieved, despite their dataset was large enough. Therefore, after implementing several models we finalized XGBOOST as the classifier for our dataset by using the sustaining classification metrics drawn. Moreover, we proudly state that our methodology bore us the highest accuracy (81%) among the other kernels on Kaggle and this is the only kernel, which makes predictions based on a single dataset (PSL only). Lastly, we aim to improve this accuracy further, built a twitter bot to tweet the predictions and hopefully a player recommender system for the PSL franchises for the upcoming drafts.

GitHub Link (Notebook): https://github.com/zaeemed/Pakistan-S…

Kaggle Notebook Link : https://www.kaggle.com/zaeemahmed/pak…

Deployment Link : https://psl-win-predictor.herokuapp.com/

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Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

• revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
• microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
• Anaconda 4.2 – Anaconda is an opensource Python package

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top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

…

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Top Machine Learning Projects in Python For Beginners [2021]

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

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Top Machine Learning Projects in Python For Beginners [2021] | upGrad blog

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

The Iris Dataset: For the Beginners

The Iris dataset is easily one of the most popular machine learning projects in Python. It is relatively small, but its simplicity and compact size make it perfect for beginners. If you haven’t worked on any machine learning projects in Python, you should start with it. The Iris dataset is a collection of flower sepal and petal sizes of the flower Iris. It has three classes, with 50 instances in every one of them.

We’ve provided sample code on various places, but you should only use it to understand how it works. Implementing the code without understanding it would fail the premise of doing the project. So be sure to understand the code well before implementing it.

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5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

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