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Deep Learning - Crash Course 2023 · LearnSpace
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Deep Learning - Crash Course 2023

Курс от Packt
Начальный≈ 18.4 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the power of deep learning and elevate your machine learning skills with our comprehensive deep neural networks course. This hands-on program covers deep learning fundamentals, including artificial neural networks, activation functions, bias, data, and loss functions. Learn Python basics focused on data science, and master tools like Matplotlib, NumPy, and Pandas for data cleaning and visualization. Progress from the MP Neuron model to the Perceptron, Sigmoid Neuron, and Universal Approximation Theorem, exploring ReLU and SoftMax activation functions. Gain practical experience with TensorFlow 2.x, creating and training deep neural networks, evaluating their performance, and fine-tuning for optimal results. By the course's end, you'll be on your way to becoming a deep-learning expert. This beginner-friendly course is perfect for students and professionals aiming to stay updated on AI. A basic understanding of programming is recommended but not required, as foundational Python skills are covered in the course.

Навыки, которые вы освоите

Artificial Neural NetworksDeep LearningPython ProgrammingTensorflowModel EvaluationData PreprocessingKeras (Neural Network Library)Model TrainingNumPyPandas (Python Package)Data ManipulationModel OptimizationMatplotlibMachine LearningArtificial IntelligenceArtificial Intelligence and Machine Learning (AI/ML)Network ModelData ScienceApplied Machine LearningMachine Learning Methods

Программа курса

17 модулей · 118 учебных материалов

01Welcome on Board3 материалов

Welcome on Board

WelcomeВидеоFull Course ResourcesЧтениеCourse IntroductionВидео
02Getting the Basics Right10 материалов

Getting the Basics Right

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

Deep Learning - Crash Course 2023
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Новые знания — в удобное для вас время.

Начать на Coursera

Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 18.4 ч

17 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Испанский, Японский, Казахский

Часть программы вашего университета
Artificial Neural NetworksВидео
Activation FunctionВидео
BiasВидео
DataВидео
Applications of DataВидео
ModelsВидео
Loss FunctionsВидео
Learning Algorithms and Model PerformanceВидео
Understanding Artificial Neural Networks and Their FunctionsDIALOGUE
Getting the Basics Right - AssessmentЗадание
03Python Crash Course on Basics9 материалов

Python Crash Course on Basics

Installing Jupyter NotebookВидеоAccessing Google ColabВидеоPython Basics - Data TypesВидеоPython Basics - Containers in PythonВидеоControl Statements Python if…elseВидеоPython Control statements - While and ForВидеоFunctions and Classes in PythonВидеоPreparing for Python Data Science with JupyterDIALOGUEPython Crash Course on Basics - AssessmentЗадание
04Python for Data Science - Crash Course10 материалов

Python for Data Science - Crash Course

NumPy Part 1ВидеоNumPy Part 2ВидеоNumPy Part 3ВидеоPandas in Python - Pandas SeriesВидеоPandas Data FrameВидеоCleaning and Examining the dataВидеоPlotting with MatplotlibВидеоContour PlotsВидеоWorking with NumPy ArraysDIALOGUEPython for Data Science - Crash Course - AssessmentЗадание
05MP Neuron Model6 материалов

MP Neuron Model

MP Neuron IntroductionВидеоIntuition of DataВидеоLoss and Finding ParametersВидеоMathematical IntuitionВидеоUtilizing the MP Neuron Model for Decision-MakingDIALOGUEMP Neuron Model - AssessmentЗадание
06MP Neuron in Python7 материалов

MP Neuron in Python

MP Neuron - Data ImportВидеоTrain Test SplitВидеоModify DataВидеоMP Neuron in PythonВидеоMP Neuron ClassВидеоImplementing MP Neuron in PythonDIALOGUEMP Neuron in Python - AssessmentЗадание
07Summary of MP Neuron3 материалов

Summary of MP Neuron

SummaryВидеоUnderstanding MP Neuron ModelDIALOGUESummary of MP Neuron - AssessmentЗадание
08Perceptron7 материалов

Perceptron

PerceptronВидеоPerceptron Model and Its RepresentationВидеоLoss Function and Parameter UpdateВидеоWhy Update Rule WorksВидеоUpdate Rule in ProgramsВидеоExploring the Perceptron ModelDIALOGUEPerceptron - AssessmentЗадание
09Perceptron in Python4 материалов

Perceptron in Python

Perceptron in PythonВидеоVisualize the Accuracy with EpochsВидеоImplementing a Perceptron for ClassificationDIALOGUEPerceptron in Python - AssessmentЗадание
10Sigmoid Neuron10 материалов

Sigmoid Neuron

Perceptron LimitationsВидеоSigmoid Neuron IntroductionВидеоSigmoid Neuron DataВидеоSigmoid IntuitionВидеоManual Fitting of DataВидеоGradient DescentВидеоProgram OverviewВидеоProgram in PythonВидеоExploring the Sigma Neuron and Gradient DescentDIALOGUESigmoid Neuron - AssessmentЗадание
11Sigmoid Neuron Implement with Python6 материалов

Sigmoid Neuron Implement with Python

Download DatasetВидеоData Standardization - 1ВидеоData Standardization - 2ВидеоClass SigmoidВидеоStandardizing Data for Sigma NeuronDIALOGUESigmoid Neuron Implement with Python - AssessmentЗадание
12Basic Probability7 материалов

Basic Probability

Introduction to Probability and Random VariablesВидеоWhy Random Variable Is ImportantВидеоRandom Variable - TypesВидеоProbability Distribution TableВидеоWhy Do We Require Entropy LossВидеоUnderstanding Probability and Random VariablesDIALOGUEBasic Probability - AssessmentЗадание
13Deep Neural Networks4 материалов

Deep Neural Networks

Why Deep Neural NetworksВидеоLinear Separation of DataВидеоUnderstanding Sigma Neuron and Linear SeparationDIALOGUEDeep Neural Networks - AssessmentЗадание
14Universal Approximation Theorem6 материалов

Universal Approximation Theorem

Understanding Universal Approximation TheoremВидеоConfirming Universal Approximation Theorem WorksВидеоGoing Deep into Neural NetworksВидеоChallenges in Creating Deep Neural Networks from ScratchВидеоUnderstanding the Universal Approximation TheoremDIALOGUEUniversal Approximation Theorem - AssessmentЗадание
15Deep Learning with TensorFlow 2.x9 материалов

Deep Learning with TensorFlow 2.x

Quick Recap on Deep LearningВидеоIntroducing TensorFlowВидеоBuilding a Neural Network with TensorFlowВидеоCreate First Neural Network with TensorFlowВидеоTraining the Neural NetworkВидеоTraining EvaluationВидеоSummaryВидеоBuilding Neural Networks with TensorFlowDIALOGUEDeep Learning with TensorFlow 2.x - AssessmentЗадание
16Activation Functions in Deep Learning Neural Networks6 материалов

Activation Functions in Deep Learning Neural Networks

Activation Functions in Deep Learning Neural Networks - IntroductionВидеоVarious Activation FunctionsВидеоSummary on Activation FunctionsВидеоCommon Network ConfigurationВидеоExploring TensorFlow Activation FunctionsDIALOGUEActivation Functions in Deep Learning Neural Networks - AssessmentЗадание
17Applying Deep Learning11 материалов

Applying Deep Learning

Moving from Shallow Learning to Deep LearningВидеоKeras BasicsВидеоTypes of ProblemsВидеоReLU, SoftMax, and Cross EntropyВидеоImplementing Multi-Class Classification Using KerasВидеоRegression ProblemВидеоTensorFlow Advanced Tricks - Ways to Create Neural NetworksВидеоTensorFlow - Subclassing MethodsВидеоApplying Deep Learning - AssessmentЗаданиеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание