Apr 09 2024 Mastering Machine Learning Algorithms using Python BaDshaH LEARNING / e-learning - Tutorials 08:38 0 Published 4/2024Created by Manas DasguptaMP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English | Duration: 108 Lectures ( 28h 34m ) | Size: 11.4 GBBuild and optimize ML Models from a range of Supervised, Unsupervised, Regression and Classification Algorithms What you'll learn:Machine Learning Core Concepts in DetailUnderstand use-case scenarios for applying Machine LearningDetailed coverage of Python for Data Science and Machine LearningRegression Algorithm - Linear RegressionClassification Problems and Classification AlgorithmsUnsupervised Learning using K-Means ClusteringExploratory Data Analysis TechniquesDimensionality Reduction Techniques (PCA)Feature Engineering TechniquesModel Optimization using Hyperparameter TuningModel Optimization using Grid-Search Cross ValidationIntroduction to Deep Neural NetworksRequirements:Some exposure to Programming Languages will be usefulDescription:Are you aspiring to become a Machine Learning Engineer or Data Scientist? if yes, then this course is for you. In this course, you will learn about core concepts of Machine Learning, use cases, role of Data, challenges of Bias, Variance and Overfitting, choosing the right Performance Metrics, Model Evaluation Techniques, Model Optmization using Hyperparameter Tuning and Grid Search Cross Validation techniques, etc. You will learn how to build Classification Models using a range of Algorithms, Regression Models and Clustering Models. You will learn the scenarios and use cases of deploying Machine Learning models. This course covers Python for Data Science and Machine Learning in great detail and is absolutely essential for the beginner in Python. Most of this course is hands-on, through completely worked out projects and examples taking you through the Exploratory Data Analysis, Model development, Model Optimization and Model Evaluation techniques.This course covers the use of Numpy and Pandas Libraries extensively for teaching Exploratory Data Analysis. In addition, it also covers Marplotlib and Seaborn Libraries for creating Visualizations. There is also an introductory lesson included on Deep Neural Networks with a worked out example on Image Classification using TensorFlow and Keras. Course Sections:Introduction to Machine LearningTypes of Machine Learning AlgorithmsUse cases of Machine LearningRole of Data in Machine LearningUnderstanding the process of Training or LearningUnderstanding Validation and TestingIntroduction to PythonSetting up your ML Development EnvironmentPython internal Data StructuresPython Language ElementsPandas Data Structure – Series and DataFramesExploratory Data Analysis - EDALearning Linear Regression Model using the House Price Prediction case studyLearning Logistic Model using the Credit Card Fraud Detection case studyEvaluating your model performanceFine Tuning your modelHyperparameter TuningCross ValidationLearning SVM through an Image Classification projectUnderstanding Decision TreesUnderstanding Ensemble Techniques using Random ForestDimensionality Reduction using PCAK-Means Clustering with Customer Segmentation ProjectIntroduction to Deep LearningWho this course is for:Begginer to Advanced Machine Learning EngineersBegginer to Advanced Data ScientistsHomepagehttps://www.udemy.com/course/mastering-machine-learning-algorithms-using-python/https://rapidgator.net/file/1f379789a87a3ff075c2eb901796acd5https://rapidgator.net/file/87c974ee7434962825b3e6fcdb7d4c59https://rapidgator.net/file/698b06c3700924ba149f36eb564db509https://rapidgator.net/file/1e0695f17883e6a9addfe7682f34b666https://rapidgator.net/file/2f9dc8067195e68b77065e2b629ccb87https://rapidgator.net/file/12e7e752780a72791d29454a95bd54e8https://rapidgator.net/file/3aaf2a341ce6c30d30538a6485a12d79https://rapidgator.net/file/d30548af7b6b4de6a6d145fbe31c3367https://rapidgator.net/file/74e1773bab7fe3eb85edf716d08cb3fahttps://rapidgator.net/file/a6fefdd6523d1c5182bf5170b44f4fadhttps://rapidgator.net/file/c539655a4c3926da117ceafdaa1fde55https://rapidgator.net/file/53cd282765938ba93a94066e77a9bfa9https://nitroflare.com/view/7F341E7A9EA68FEhttps://nitroflare.com/view/94AA8DF4C127A33https://nitroflare.com/view/25C82932D1E3008https://nitroflare.com/view/8141E3027991D7Ahttps://nitroflare.com/view/6B4AADC5A15F18Fhttps://nitroflare.com/view/84D8F4B64A823E0https://nitroflare.com/view/8916C166F32D7D4https://nitroflare.com/view/4B78676FD4390BFhttps://nitroflare.com/view/57EA14385E9BD43https://nitroflare.com/view/0F98E9F0C4011A8https://nitroflare.com/view/2DFC8D95A5116D8https://nitroflare.com/view/FB8319147642F44 Related News Deep Learning: Python Deep Learning MasterclassUdemy - Complete Machine Learning & Data Science with Python | A-ZPython & Data Science with R | Python & R ProgrammingThe Complete Visual Guide To Machine Learning & Data SciencePython Mastery For Data, Statistics & Statistical Modeling Comments (0)Add comment Submit NEWEST RELEASES 01.05: PrimaToon 2.1.2 Portable 01.05: Perfectly Clear WorkBench 4.6.1.2658 (x64) Multilingual Portable 01.05: TeraCopy Pro 3.17 Multilingual Portable 01.05: MouseBoost Pro 3.4.1 macOS 01.05: Perfectly Clear WorkBench 4.6.1.2658 macOS 01.05: Aiseesoft iPhone Unlocker 2.0.56 macOS 01.05: Pixelmator Pro 3.5.11 macOS 01.05: Topaz Gigapixel AI 7.1.4 (x64) Portable 01.05: Freemake Video Converter 4.1.13.173 Multilingual Portabhle 01.05: Auslogics Windows Slimmer Professional 4.0.0.5 Multilingual Portable Recommended Filehosts Freinds Site