Deep Learning for Everyone – 2023 – Tensorflow Updated

سرفصل های دوره

Go from Beginner to Expert with building intuition on single neuron till deep neural networks in Keras & tensorflow

01 - Welcome

001 Introduction to Deep Learning 101

02 - Getting basics right

001 Artificial Neural Networks

002 Activation Function

003 Bias

004 Data

005 Applications of Data

006 Models

007 Loss Functions

008 Learning Algorithms & Model Performance

03 - Python Crash Course on Basics

001 Getting System Ready - Jupyter Notebook

002 Accessing Google Colab Notebook

003 Download Materials.html

003 Python-Crash-Course.zip

004 Python Basics - Data Types

005 Python Basics - Containers in Python

006 Control Statements Python if..else

007 Python Control statments - While and For

008 Functions & Classes in Python

04 - Python for Data Science Crash Course

001 Numpy Part 1

002 Numpy Part 2

003 Numpy Part 3

004 Pandas in Python - Pandas Series

005 Pandas Data Frame

006 Pandas Data frame - cleaning & Examining the data

007 Plotting with Matplotlib

008 Contour Plots

05 - MP Neuron Model

001 MP Neuron Introduction

002 Intuition of data

003 Loss & finding parameters

004 Mathematical Intuition

06 - MP Neuron in Python

001 Deep-Learning-MP-Neuron.zip

001 Download Materials.html

002 MP Neuron - Data import

003 Train Test Split

004 Modify Data

005 MP Neuron in Python

006 MP Neuron Class

007 Assignment for MP Neuron in Python.html

007 MP-Neuron-Assignment.zip

07 - Summary of MP Neuron

001 Summary of MP Neuron

08 - Perceptron

001 Perceptron

002 Perceptron Model and its representation

003 Loss function & Parameter Update

004 Why Update Rule Works

005 Update Rule in Programs

09 - Perceptron in Python

001 Download Materials.html

001 Perceptron-Implementation.zip

002 Perceptron in Python

003 Visualize the Accuracy with epochs

004 Perceptron Assignment.html

004 Perceptron-Assignment.zip

10 - Sigmoid Neuron

001 Download Materials.html

001 Sigmoid-Neuron-Intuition.zip

002 Percepron Limitations

003 Sigmoid Neuron Introduction

004 Sigmoid Neuron Data

005 Sigmoid Intuition

006 Manual fitting of data

007 Gradient descent

008 Program overview

009 Program in Python

11 - Sigmoid Neuron Implement with Python

001 Download Materials.html

001 Sigmoid-Neuron-Heart-Disease-dataset.zip

002 Download Dataset

002 heart-disease-uci.zip

003 Data Standardization -1

004 Data Standardization - 2

005 Class Sigmoid

006 Sigmoid Assignment.html

006 Sigmoid-Neuron-Assignment.zip

12 - Basic Probability

001 Introduction to Probability and Random Variables

002 Why Random Variable is important

003 Random Variable - Types

004 Probability Distribution Table

005 Why do we require Entropy Loss

13 - Why Deep Neural Networks - Intuition

001 Download Materials.html

001 Why-DeepLearning-Neural-Networks.zip

002 Why Deep Neural Networks

003 Linear Separation of Data

14 - Universal Approximation Theorem - Deep Learning Foundation

001 Understanding Universal Approximation Theorem

002 Confirming Universal Approximation Theorem Works

003 Going deep into Neural Networks

004 Challenges in Creating Deep Neural Networks from Scratch

15 - Deep Learning with Tensorflow 2.x

001 1-creating-first-nn-with-tf-2-x.zip

001 Code File for this section.html

002 Deep Neural Networks - Recap

003 Introducing Tensorflow

004 Building a Neural Network with Tensorflow

005 Create First Neural Network with Tensorflow

006 Training the Deep Neural Network

007 Training Evaluation

008 Summary

16 - Activation Functions in Deep Learning Neural Networks

001 Code File for this Section.html

001 activation-functions-in-tensorflow.zip

002 Activation Functions in Deep Learning Neural Networks - Introduction

003 Various Activation Functions

004 Summary on Activation Functions

005 Common Network Configuration

17 - Applying the Deep learning

001 Moving from Shallow learning to Deep learning

002 Assignment File for Deep learning neural networks.html

002 Assignment-File-for-DeepLearning-Neural-Networks.zip

003 Keras Basics

004 DeepLearning-Multi-Class-Classification.zip

004 Deep-Learning-Regression.zip

004 Download Materials.html

005 Types of Problems

006 ReLU , Softmax & Cross Entropy

007 DeepLearning-Multi-Class-Classification.zip

007 Implementing Multi Class classification using keras

008 Deep-Learning-Regression.zip

008 Regression Problem

009 Tensorflow Advanced Tricks - Ways to create Neural Network

010 Tensorflow - Subclassing Methods

011 Bonus - Get More of Learning Journey.html

18 - Machine Learning for Projects

001 Machine learning Deployment Part 1 - Model Prep - End to End

002 Machine learning Deployment Part 2 - Deploy Flask App - End to End

003 Streamlit Tutorial

004 Additional content to support your learning journey.html

005 Course Intro to MLOps

189,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy