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Learning Python by Mark Lutz

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1Learning Python

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  • Title: Learning Python
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1266.12 Mbs, the file-s for this book were downloaded 556 times, the file-s went public at Thu Jul 01 2021.

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2Algorithmic Trading A Z With Python And Machine Learning

Algorithmic Trading A-Z with Python and Machine Learning

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The book is available for download in "data" format, the size of the file-s is: 10176.21 Mbs, the file-s for this book were downloaded 149 times, the file-s went public at Wed Jan 13 2021.

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3Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (11 - Random Forest Regression)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (11 - Random Forest Regression)

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The book is available for download in "movies" format, the size of the file-s is: 71.10 Mbs, the file-s for this book were downloaded 60 times, the file-s went public at Sat Feb 10 2024.

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4Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (14 - Regression Model Selection In R)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (14 - Regression Model Selection in R)

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The book is available for download in "movies" format, the size of the file-s is: 40.79 Mbs, the file-s for this book were downloaded 40 times, the file-s went public at Sat Feb 10 2024.

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5Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (16 - Logistic Regression)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (16 - Logistic Regression)

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  • Title: ➤  Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (16 - Logistic Regression)

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The book is available for download in "movies" format, the size of the file-s is: 246.99 Mbs, the file-s for this book were downloaded 75 times, the file-s went public at Sat Feb 10 2024.

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6Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (27 - Hierarchical Clustering)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (27 - Hierarchical Clustering)

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The book is available for download in "movies" format, the size of the file-s is: 153.82 Mbs, the file-s for this book were downloaded 59 times, the file-s went public at Sat Feb 10 2024.

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7Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (42 - Part 10 Model Selection & Boosting)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (42 - Part 10 Model Selection & Boosting)

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The book is available for download in "data" format, the size of the file-s is: 0.02 Mbs, the file-s for this book were downloaded 30 times, the file-s went public at Sat Feb 10 2024.

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8Deep Learning From Scratch With Python

deep learing

“Deep Learning From Scratch With Python” Metadata:

  • Title: ➤  Deep Learning From Scratch With Python

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The book is available for download in "audio" format, the size of the file-s is: 896.10 Mbs, the file-s for this book were downloaded 3 times, the file-s went public at Mon Jun 16 2025.

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9Bayesian Machine Learning In Python AB Testing

Bayesian Machine Learning In Python AB Testing

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  • Title: ➤  Bayesian Machine Learning In Python AB Testing

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The book is available for download in "data" format, the size of the file-s is: 1396.04 Mbs, the file-s for this book were downloaded 166 times, the file-s went public at Sat Aug 15 2020.

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10Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (18 - Support Vector Machine (SVM))

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (18 - Support Vector Machine (SVM))

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  • Title: ➤  Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (18 - Support Vector Machine (SVM))

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The book is available for download in "movies" format, the size of the file-s is: 78.53 Mbs, the file-s for this book were downloaded 45 times, the file-s went public at Sat Feb 10 2024.

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11How To Think Like A Computer Scientist Learning Python

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How To Think Like A Computer Scientist Learning Python

“How To Think Like A Computer Scientist Learning Python” Metadata:

  • Title: ➤  How To Think Like A Computer Scientist Learning Python
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 92.29 Mbs, the file-s for this book were downloaded 49 times, the file-s went public at Wed Oct 04 2023.

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12Supervised Machine Learning With Python Logistic Regression

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Machine Learning With Python- Logistic Regression. This article demonstrates how to utilize the logistic regression classification algorithm in Python.

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  • Title: ➤  Supervised Machine Learning With Python Logistic Regression
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1.45 Mbs, the file-s for this book were downloaded 23 times, the file-s went public at Mon Mar 25 2024.

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13Unsupervised Machine Learning With Python KMeans Clustering

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This article will provide us with insight and a practical example of Unsupervised Machine Learning using Python. Specifically, we will look at the K-Means Clustering algorithm in the domain of machine learning.

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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1.80 Mbs, the file-s for this book were downloaded 19 times, the file-s went public at Mon Mar 25 2024.

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14The Complete Python, Machine Learning, AI Mega Bundle

"The Complete Python, Machine Learning, AI Mega Bundle is a comprehensive collection of courses and resources covering Python programming, machine learning, and artificial intelligence. It is designed to guide learners from beginner to advanced levels, encompassing Python fundamentals, data manipulation, statistical analysis, machine learning algorithms, deep learning, and natural language processing."

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  • Title: ➤  The Complete Python, Machine Learning, AI Mega Bundle

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The book is available for download in "texts" format, the size of the file-s is: 3.61 Mbs, the file-s for this book were downloaded 122 times, the file-s went public at Thu Feb 01 2024.

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15Andrew Park Data Science For Beginners 4 Books In 1 Python Programming, Data Analysis, Machine Learning. A Complete Overview To Master The Art Of Data Science From Scratch Using Python For Busines

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random2, 'Andrew Park - Data Science for Beginners_ 4 Books in 1_ Python Programming, Data Analysis, Machine Learning. A Complete Overview to Master The Art of Data Science From Scratch Using Python for Busines'

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  • Title: ➤  Andrew Park Data Science For Beginners 4 Books In 1 Python Programming, Data Analysis, Machine Learning. A Complete Overview To Master The Art Of Data Science From Scratch Using Python For Busines
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The book is available for download in "texts" format, the size of the file-s is: 217.58 Mbs, the file-s for this book were downloaded 27 times, the file-s went public at Sat May 04 2024.

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16DFSP # 212 - Learning Python

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This week I review resources aimed at teaching you Python

“DFSP # 212 - Learning Python” Metadata:

  • Title: DFSP # 212 - Learning Python
  • Author: ➤  

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The book is available for download in "audio" format, the size of the file-s is: 7.03 Mbs, the file-s for this book were downloaded 5 times, the file-s went public at Sun Mar 21 2021.

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17Mastering Git Switch, Python Learning Sites, And Debugging Ruby On Rails

"Mastering Git Switch, Python Learning Sites, and Debugging Ruby on Rails" is a comprehensive guide for developers aiming to enhance their skills in essential areas of modern software development. This blog covers three critical topics: mastering the git switch command in Git for efficient branch management, exploring the best Python learning sites for programmers, and delving into advanced debugging techniques for Ruby on Rails applications. Whether you're navigating version control, expanding your programming knowledge, or tackling complex Rails bugs, this guide offers valuable insights and practical tips to boost your productivity and expertise. Read more -  https://stackify.com/

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  • Title: ➤  Mastering Git Switch, Python Learning Sites, And Debugging Ruby On Rails
  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 2.35 Mbs, the file-s for this book were downloaded 11 times, the file-s went public at Fri Sep 20 2024.

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18Crypto Currency Price Prediction With Machine Learning Using Python

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We use and study a wide range of machine learning methods to predict and trade in the daily crypto currency market. We teach the algorithms to make daily market predictions based on how the 100 cryptocurrencies with the most market value change in price. Based on our research, all of the used models are able to make estimates that are statistically sound, with the average accuracy of all crypto currencies falling between 52.9% and 54.1%. When these accurate numbers are based on the 10% most confident expectations for each class and day, they go up to somewhere between 57.5% and 59.5%. A well-known case study in the field of data science looks at how people try to figure out how much different digital currencies are worth. Stock prices and the prices of cryptocurrencies are based on more than just the amount of buy and sell orders. At the moment, the government's financial policies about digital currencies affect how the prices of these things change. People's views about a crypto currency or a star who directly or indirectly backs a crypto currency can also cause a big rise in buying and selling of that currency. This study looks at the trustworthiness of the three most famous coins on the market today: bitcoin, how well buying strategies for ethereum and litecoin that are based on machine learning work. The models are checked and tested with both good and bad market situations. This lets us figure out how accurate the forecasts are in light of any changes in how the market feels between the proof and test times.

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  • Title: ➤  Crypto Currency Price Prediction With Machine Learning Using Python
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The book is available for download in "texts" format, the size of the file-s is: 6.85 Mbs, the file-s for this book were downloaded 34 times, the file-s went public at Sat Sep 21 2024.

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19Free Course Site.com Udemy Machine Learning A Z™ Hands On Python & R In Data Science

Course in Machine Learning and Data Science

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The book is available for download in "data" format, the size of the file-s is: 0.20 Mbs, the file-s for this book were downloaded 9 times, the file-s went public at Fri Aug 20 2021.

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20Mastering Machine Learning With Python In Six Steps : A Practical Implementation Guide To Predictive Data Analytics Using Python

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Course in Machine Learning and Data Science

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  • Title: ➤  Mastering Machine Learning With Python In Six Steps : A Practical Implementation Guide To Predictive Data Analytics Using Python
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 1059.46 Mbs, the file-s for this book were downloaded 271 times, the file-s went public at Fri Nov 04 2022.

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21Introduction To Machine Learning With Python ( PDFDrive.com )

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My library

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The book is available for download in "texts" format, the size of the file-s is: 7089.26 Mbs, the file-s for this book were downloaded 5179 times, the file-s went public at Wed Feb 03 2021.

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22Introduction To Machine Learning With Python ( PDFDrive.com )

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books

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The book is available for download in "texts" format, the size of the file-s is: 7370.03 Mbs, the file-s for this book were downloaded 4383 times, the file-s went public at Thu Feb 25 2021.

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23Learning To Learn Python

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“Learning To Learn Python” Metadata:

  • Title: Learning To Learn Python

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The book is available for download in "movies" format, the size of the file-s is: 212.78 Mbs, the file-s for this book were downloaded 279 times, the file-s went public at Fri Sep 23 2016.

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24Reinforcement Learning With Python : Master Reinforcement Learning In Python Without Being An Expert

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48 pages ; 28 cm

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The book is available for download in "texts" format, the size of the file-s is: 116.00 Mbs, the file-s for this book were downloaded 76 times, the file-s went public at Sat Jun 11 2022.

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25Graph-based Active Learning Of Agglomeration (GALA): A Python Library To Segment 2D And 3D Neuroimages.

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This article is from Frontiers in Neuroinformatics , volume 8 . Abstract The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them.

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  • Title: ➤  Graph-based Active Learning Of Agglomeration (GALA): A Python Library To Segment 2D And 3D Neuroimages.
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  • Language: English

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The book is available for download in "texts" format, the size of the file-s is: 6.62 Mbs, the file-s for this book were downloaded 166 times, the file-s went public at Thu Oct 23 2014.

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26Hak5 - Learning Python, VBS Scripts And Trivia! Hak5 1022.3

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This time on the show, pound include programming dot h! We're going to void main and Hello World all up in this biznitch. Python, JavaScript, BASIC? It's time to learn to code! All that and more this time on Hak5............return zero Source: https://www.youtube.com/watch?v=AmNZwW6833U Uploader: Hak5

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The book is available for download in "movies" format, the size of the file-s is: 149.95 Mbs, the file-s for this book were downloaded 86 times, the file-s went public at Tue Jul 09 2019.

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27PYTHON : L'ESSENTIEL POUR MACHINE LEARNING - ML#7

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Introduction à la programmation Python pour faire du Machine Learning. Python est un langage interprété, et c'est le meilleur pour faire du Machine Learning en 2019 : il contient le plus de fonctionnalité et de ressource pour exceller en Machine Learning et en Deep Learning. Google, Facebook, Amazon utilisent tous Python pour leurs initiatives d'intelligence artificielle. Dans cette vidéo, je vous montre les structures de contrôle de base qu'il faut maîtriser pour écrire des algorithmes de machine learning. ► Timecode de la vidéo : 00:00 : Début 0:26 : Introduction 1:58 : Les Bases de Python 2:57 : Commentaires, Variables, Print 5:04 : IF - ELIF - ELSE 7:42 : Astuce Bonus 8:10 : Jupyter Notebook 9:27 : FOR LOOP 10:40 : WHILE LOOP 12:10 : Importer des Modules 14:02 : Créer nos propres fonctions ► Lien pour télécharger Anaconda : https://www.anaconda.com ► ARTICLE EN COMPLÉMENT DE CETTE VIDÉO: https://machinelearnia.com/ ► Soutenez-moi sur Tipeee pour du contenu BONUS: https://fr.tipeee.com/machine-learnia ► REJOINS NOTRE COMMUNAUTÉ DISCORD https://discord.gg/WMvHpzu ► Recevez gratuitement mon Livre: APPRENDRE LE MACHINE LEARNING EN UNE SEMAINE CLIQUEZ ICI: https://machinelearnia.com/apprendre-le-machine-learning-en-une-semaine/ ► Pour En Savoir plus : Visitez Machine Learnia : https://machinelearnia.com/ ► Qui suis-je ? Je m’appelle Guillaume Saint-Cirgue et je suis Data Scientist au Royaume Uni. Après avoir suivi un parcours classique maths sup maths spé et avoir intégré une bonne école d’ingénieur, je me suis tourné vers l’intelligence artificielle de ma propre initiative et j’ai commencé à apprendre tout seul le machine learning et le deep learning en suivant des formations payantes, en lisant des articles scientifiques, en suivant les cours du MIT et de Stanford et en passant des week end entier à développer mes propres codes. Aujourd’hui, je veux vous offrir ce que j’ai appris gratuitement car le monde a urgemment besoin de se former en Intelligence Artificielle. Que vous souhaitiez changer de vie, de carrière, ou bien développer vos compétences à résoudre des problèmes, ma chaîne vous y aidera. C’est votre tour de passer à l’action ! ► Une question ? Contactez-moi: [email protected]

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28NASA Technical Reports Server (NTRS) 20220003102: MLtool: Universal Supervised Machine Learning Tool To Model Tabulated Data MLtool Python Code

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Machine Learning (ML) is a subfield of Artificial Intelligence that gives computers the ability to learn from past data without being explicitly programmed. The predictive capabilities of ML models have already been used to facilitate several scientific breakthroughs. However, the practical application of ML is often limited due to the gaps in technical knowledge of its users. The common issue faced by many scientific researchers is the inability to choose the appropriate ML pipelines that are needed to treat real-world data, which is often sparse and noisy. To solve this problem, we have developed an automated Machine Learning tool (MLtool) that includes a set of ML algorithms and approaches to aid scientific researchers. The current version of MLtool is implemented as an object-oriented Python code that is easily extensible. It includes 44 different regression algorithms used to model data. MLtool helps users select the best model for their data, based on the scoring metrics used. Besides regression algorithms, MLtool also includes a suite of pre- and post-processing techniques such as missing value imputation, categorical variable encoding, input feature normalization, uncertainty quantification, exploratory data analysis (EDA), etc. MLtool was tested on several publicly available multi-dimensional data sets and was found capable of making accurate predictions.

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29A Framework For Distributed Deep Learning Layer Design In Python

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In this paper, a framework for testing Deep Neural Network (DNN) design in Python is presented. First, big data, machine learning (ML), and Artificial Neural Networks (ANNs) are discussed to familiarize the reader with the importance of such a system. Next, the benefits and detriments of implementing such a system in Python are presented. Lastly, the specifics of the system are explained, and some experimental results are presented to prove the effectiveness of the system.

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30Come Organizzare La Struttura Di Un Progetto Python O Machine Learning

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In questo video parleremo di un tema molto importante: come strutturare correttamente un progetto Python o Machine Learning.Strutturare correttamente un progetto Python serve prima di tutto a dare un senso a quello che state facendo e a rendere il codice immediatamente comprensibile, soprattutto a distanza di tempo, per poi stessi e anche per chi dovrà lavorare al vostro stesso progetto e quindi al vostro codice.Infatti, se avete del codice abbastanza \"incasinato\" e non strutturato correttamente, nel caso qualcuno (collaboratore, amico, conoscente, ecc.) dovesse aiutarvi nella ricerca di bugs o nell'implementazione di nuove funzionalità, dovrà prima di tutto capire come funziona il vostro programma, quali sono i flussi del software e come esso e organizzato. Risulterà quindi un'enorme perdita di tempo. Invece di concentrarvi nella vera risoluzione di un bug, dovrete prima di tutto cercare di capire come funziona il codice.Un progetto ben strutturato, e quindi anche un codice ben organizzato, vi consentirà un agevole refactor e un'agevole implementazione di nuove funzionalità.

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31Deep Learning In Python

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Tobias Brandt https://2016.za.pycon.org/talks/16/ This talk will give an introduction to Neural Networks and Deep Learning in Python. We will cover some of the history of Neural Networks and obstacles that were encountered in the 1990s. This will then lead onto the developments in 2006 and 2012 that lead to the resurgence of interest in Neural Networks and the rebranding of the field as Deep Learning. These developments will be illustrated by means of an extended example of building a classifier of hand written digits on the MNIST dataset. We will start with a simple Multi-Layer Perceptron and then build this up into a Stacked Denoising Autoencoder. All code will be developed using the Keras framework and TensorFlow and can be run on a simple laptop.

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32Learning Python By Mark Lutz

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33PJ2T-VYTP: Video Analysis Using Python | Deep Learning On Vi…

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34Introduction To Machine Learning With Python

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35[LinkedInx Learning] - Descubra O Python

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36Learning Python Manual (4th Edition)(Chinese Edition)

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37[LinkedInx Learning] - Técnicas Avançadas De Python

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38Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (38 - Part 9 Dimensionality Reduction)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (38 - Part 9 Dimensionality Reduction)

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39Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (41 - Kernel PCA)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (41 - Kernel PCA)

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40Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (01 - Welcome To The Course! Here We Will Help You Get Started In The Best Conditions)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (01 - Welcome to the course! Here we will help you get started in the best conditions)

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41Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (02 - Part 1 Data Preprocessing)

Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (02 - Part 1 Data Preprocessing)

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42Learning Data Mining With Python : Harness The Power Of Python To Analyze Data And Create Insightful Predictive Models

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Machine Learning A-Z AI, Python & R + ChatGPT Bonus 2023 (02 - Part 1 Data Preprocessing)

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43A Machine Learning Approach In Python Is Used To Forecast The Number Of Train Passengers Using A Fuzzy Time Series Model

Train passenger forecasting assists in planning, resource use, and system management. forecasts rail ridership. Train passenger predictions help prevent stranded passengers and empty seats. Simulating rail transport requires a low-error model. We developed a fuzzy time series forecasting model. Using historical data was the goal. This concept predicts future railway passengers using Holt's double exponential smoothing (DES) and a fuzzy time series technique based on a rate-of-change algorithm. Holt's DES predicts the next period using a fuzzy time series and the rate of change. This method improves prediction accuracy by using event discretization. positive, since changing dynamics reveal trends and seasonality. It uses event discretization and machine-learning-optimized frequency partitioning. The suggested method is compared to existing train passenger forecasting methods. This study has a low average forecasting error and a mean squared error.

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44Unsupervised Machine Learning With Python Mean Shift Algorithm

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This article explains and demonstrates the Mean Shift Algorithm in Python which is an Unsupervised Classification Machine Learning algorithm.

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45Python Machine Learning From Scratch : Machine Learning Concepts And Applications For Beginners

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130 pages : 23 cm

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46Python Machine Learning

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47Python Machine Learning Case Studies : Five Case Studies For The Data Scientist

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48[ Reading] After Work Data Science Ensemble Learning With Python

[ Reading] After Work Data Science Ensemble Learning With Python

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49Machine Learning, Data Science And Deep Learning With Python

Machine Learning, Data Science And Deep Learning With Python

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50Introduction To Machine Learning With Python

aibot machine learning

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1Learning Python

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  • Languages: English - ger
  • Number of Pages: Median: 591
  • Publisher: ➤  O'Reilly Media - O'Reilly Media, Incorporated - O'Reilly - Shroff Publishers & Distributors Pvt. Ltd. - CreateSpace Independent Publishing Platform - O'Reilly Media, Inc.
  • Publish Date: ➤  
  • Publish Location: ➤  Sebstopol - Sebastopol, CA - Cambridge - Taipei - Tokyo - Farnham - Paris - Köln - Beijing - CA 95472

“Learning Python” Subjects and Themes:

Edition Identifiers:

First Setence:

"Dieses Buch bietet Ihnen eine kurze Einführung in die Programmiersprache Python."

Access and General Info:

  • First Year Published: 1999
  • Is Full Text Available: Yes
  • Is The Book Public: No
  • Access Status: Borrowable

Online Access

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The book is not public therefore the download links will not allow the download of the entire book, however, borrowing the book online is available.

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2Learning Python Manual (4th edition)(Chinese Edition)

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“Learning Python Manual (4th edition)(Chinese Edition)” Metadata:

  • Title: ➤  Learning Python Manual (4th edition)(Chinese Edition)
  • Author:
  • Publisher: Machinery Industry Press
  • Publish Date:

Edition Identifiers:

Access and General Info:

  • First Year Published: 2011
  • Is Full Text Available: Yes
  • Is The Book Public: No
  • Access Status: Borrowable

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The book is not public therefore the download links will not allow the download of the entire book, however, borrowing the book online is available.

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Available audio books for downloads from LibriVox

1Susan B. Anthony Rebel, Crusader, Humanitarian

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Book's cover

Alma Lutz's outstanding biography of Susan B. Anthony is revered for its descriptive power, attention to detail and historical significance to the women's Suffragette movement. - Summary by PhyllisV

“Susan B. Anthony Rebel, Crusader, Humanitarian” Metadata:

  • Title: ➤  Susan B. Anthony Rebel, Crusader, Humanitarian
  • Author:
  • Language: English
  • Publish Date:

Edition Specifications:

  • Format: Audio
  • Number of Sections: 26
  • Total Time: 14:16:52

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  • LibriVox Link:
  • Text Source: - Download text file/s.
  • Number of Sections: 26 sections

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  • File Name: susanbanthony_2004_librivox
  • File Format: zip
  • Total Time: 14:16:52
  • Download Link: Download link

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