وب سایت تخصصی شرکت فرین
دسته بندی دوره ها
1

Artificial Intelligence with Machine Learning, Deep Learning

سرفصل های دوره

Artificial Intelligence (AI) with Python Machine Learning and Python Deep Learning, Transfer Learning, Tensorflow


1 - Numpy
  • 1 - Installing Anaconda Distribution for Windows
  • 2 - Notebook Project Files Link regarding NumPy Python Programming Language Library.html
  • 3 - Installing Anaconda Distribution for MacOs
  • 4 - 6 Article Advice And Links about Numpy Numpy Pyhon.html
  • 5 - Installing Anaconda Distribution for Linux
  • 6 - Introduction to NumPy Library
  • 7 - The Power of NumPy
  • 8 - Creating NumPy Array with The Array Function
  • 9 - Creating NumPy Array with Zeros Function
  • 10 - Creating NumPy Array with Ones Function
  • 11 - Creating NumPy Array with Full Function
  • 12 - Creating NumPy Array with Arange Function
  • 13 - Creating NumPy Array with Eye Function
  • 14 - Creating NumPy Array with Linspace Function
  • 15 - Creating NumPy Array with Random Function
  • 16 - Properties of NumPy Array
  • 17 - Identifying the Largest Element of a Numpy Array
  • 18 - Detecting Least Element of Numpy Array Min Ar
  • 19 - Reshaping a NumPy Array Reshape Function
  • 20 - Concatenating Numpy Arrays Concatenate Functio
  • 21 - Splitting OneDimensional Numpy Arrays The Split
  • 22 - Splitting TwoDimensional Numpy Arrays Split
  • 23 - Sorting Numpy Arrays Sort Function
  • 24 - Indexing Numpy Arrays
  • 25 - Slicing OneDimensional Numpy Arrays
  • 26 - Slicing TwoDimensional Numpy Arrays
  • 27 - Assigning Value to OneDimensional Arrays
  • 28 - Assigning Value to TwoDimensional Array
  • 29 - Fancy Indexing of OneDimensional Arrrays
  • 30 - Fancy Indexing of TwoDimensional Arrrays
  • 31 - Combining Fancy Index with Normal Indexing
  • 32 - Combining Fancy Index with Normal Slicing
  • 33 - Operations with Comparison Operators
  • 34 - Arithmetic Operations in Numpy
  • 35 - Statistical Operations in Numpy
  • 36 - Solving SecondDegree Equations with NumPy

  • 2 - Pandas
  • 37 - Pandas Project Files Link.html
  • 38 - Introduction to Pandas Library
  • 39 - Creating a Pandas Series with a List
  • 40 - Creating a Pandas Series with a Dictionary
  • 41 - Creating Pandas Series with NumPy Array
  • 42 - Object Types in Series
  • 43 - Examining the Primary Features of the Pandas Seri
  • 44 - Most Applied Methods on Pandas Series
  • 45 - Indexing and Slicing Pandas Series
  • 46 - Creating Pandas DataFrame with List
  • 47 - Creating Pandas DataFrame with NumPy Array
  • 48 - Creating Pandas DataFrame with Dictionary
  • 49 - Examining the Properties of Pandas DataFrames
  • 50 - Element Selection Operations in Pandas DataFrames Lesson 1
  • 51 - Element Selection Operations in Pandas DataFrames Lesson 2
  • 52 - Top Level Element Selection in Pandas DataFramesLesson 1
  • 53 - Top Level Element Selection in Pandas DataFramesLesson 2
  • 54 - Top Level Element Selection in Pandas DataFramesLesson 3
  • 55 - Element Selection with Conditional Operations in Pandas Data Frames
  • 56 - Adding Columns to Pandas Data Frames
  • 57 - Removing Rows and Columns from Pandas Data frames
  • 58 - Null Values in Pandas Dataframes
  • 59 - Dropping Null Values Dropna Function
  • 60 - Filling Null Values Fillna Function
  • 61 - Setting Index in Pandas DataFrames
  • 62 - MultiIndex and Index Hierarchy in Pandas DataFrames
  • 63 - Element Selection in MultiIndexed DataFrames
  • 64 - Selecting Elements Using the xs Function in MultiIndexed DataFrames
  • 65 - Concatenating Pandas Dataframes Concat Function
  • 66 - Merge Pandas Dataframes Merge Function Lesson 1
  • 67 - Merge Pandas Dataframes Merge Function Lesson 2
  • 68 - Merge Pandas Dataframes Merge Function Lesson 3
  • 69 - Merge Pandas Dataframes Merge Function Lesson 4
  • 70 - Joining Pandas Dataframes Join Function
  • 71 - Loading a Dataset from the Seaborn Library
  • 72 - Examining the Data Set 1
  • 73 - Aggregation Functions in Pandas DataFrames
  • 74 - Examining the Data Set 2
  • 75 - Coordinated Use of Grouping and Aggregation Functions in Pandas Dataframes
  • 76 - Advanced Aggregation Functions Aggregate Function
  • 77 - Advanced Aggregation Functions Filter Function
  • 78 - Advanced Aggregation Functions Transform Function
  • 79 - Advanced Aggregation Functions Apply Function
  • 80 - Examining the Data Set 3
  • 81 - Pivot Tables in Pandas Library
  • 82 - Accessing and Making Files Available
  • 83 - Data Entry with Csv and Txt Files
  • 84 - Data Entry with Excel Files
  • 85 - Outputting as an CSV Extension
  • 86 - Outputting as an Excel File

  • 3 - First Contact with Machine Learning
  • 87 - What is Machine Learning
  • 88 - Machine Learning Terminology
  • 89 - Project Files Link.html

  • 4 - Evalution Metrics in Machine Learning
  • 90 - Classification vs Regression in Machine Learning
  • 91 - Machine Learning Model Performance Evaluation Classification Error Metrics
  • 92 - Evaluating Performance Regression Error Metrics in Python
  • 93 - Machine Learning With Python

  • 5 - Supervised Learning with Machine Learning
  • 94 - What is Supervised Learning in Machine Learning

  • 6 - Linear Regression Algorithm in Machine Learning AZ
  • 95 - Linear Regression Algorithm Theory in Machine Learning AZ
  • 96 - Linear Regression Algorithm With Python Part 1
  • 97 - Linear Regression Algorithm With Python Part 2
  • 98 - Linear Regression Algorithm With Python Part 3
  • 99 - Linear Regression Algorithm With Python Part 4

  • 7 - Bias Variance TradeOff in Machine Learning
  • 100 - What is Bias Variance TradeOff

  • 8 - Logistic Regression Algorithm in Machine Learning AZ
  • 101 - What is Logistic Regression Algorithm in Machine Learning
  • 102 - Logistic Regression Algorithm with Python Part 1
  • 103 - Logistic Regression Algorithm with Python Part 2
  • 104 - Logistic Regression Algorithm with Python Part 3
  • 105 - Logistic Regression Algorithm with Python Part 4
  • 106 - Logistic Regression Algorithm with Python Part 5

  • 9 - Kfold CrossValidation in Machine Learning AZ
  • 107 - KFold CrossValidation Theory
  • 108 - KFold CrossValidation with Python

  • 10 - K Nearest Neighbors Algorithm in Machine Learning AZ
  • 109 - K Nearest Neighbors Algorithm Theory
  • 110 - K Nearest Neighbors Algorithm with Python Part 1
  • 111 - K Nearest Neighbors Algorithm with Python Part 2
  • 112 - K Nearest Neighbors Algorithm with Python Part 3

  • 11 - Hyperparameter Optimization
  • 113 - Hyperparameter Optimization Theory
  • 114 - Hyperparameter Optimization with Python

  • 12 - Decision Tree Algorithm in Machine Learning AZ
  • 115 - Decision Tree Algorithm Theory
  • 116 - Decision Tree Algorithm with Python Part 1
  • 117 - Decision Tree Algorithm with Python Part 2
  • 118 - Decision Tree Algorithm with Python Part 3
  • 119 - Decision Tree Algorithm with Python Part 4
  • 120 - Decision Tree Algorithm with Python Part 5

  • 13 - Random Forest Algorithm in Machine Learning AZ
  • 121 - Random Forest Algorithm Theory
  • 122 - Random Forest Algorithm with Pyhon Part 1
  • 123 - Random Forest Algorithm with Pyhon Part 2

  • 14 - Support Vector Machine Algorithm in Machine Learning AZ
  • 124 - Support Vector Machine Algorithm Theory
  • 125 - Support Vector Machine Algorithm with Python Part 1
  • 126 - Support Vector Machine Algorithm with Python Part 2
  • 127 - Support Vector Machine Algorithm with Python Part 3
  • 128 - Support Vector Machine Algorithm with Python Part 4

  • 15 - Unsupervised Learning
  • 129 - Unsupervised Learning Overview

  • 16 - K Means Clustering Algorithm in Machine Learning AZ
  • 130 - K Means Clustering Algorithm Theory
  • 131 - K Means Clustering Algorithm with Python Part 1
  • 132 - K Means Clustering Algorithm with Python Part 2
  • 133 - K Means Clustering Algorithm with Python Part 3
  • 134 - K Means Clustering Algorithm with Python Part 4

  • 17 - Hierarchical Clustering Algorithm in Machine Learning AZ
  • 135 - Hierarchical Clustering Algorithm Theory
  • 136 - Hierarchical Clustering Algorithm with Python Part 1
  • 137 - Hierarchical Clustering Algorithm with Python Part 2

  • 18 - Principal Component Analysis PCA in Machine Learning AZ
  • 138 - Principal Component Analysis PCA Theory
  • 139 - Principal Component Analysis PCA with Python Part 1
  • 140 - Principal Component Analysis PCA with Python Part 2
  • 141 - Principal Component Analysis PCA with Python Part 3

  • 19 - Recommender System Algorithm in Machine Learning AZ
  • 142 - What is the Recommender System Part 1
  • 143 - What is the Recommender System Part 2

  • 20 - Machine Learning Recap And First Contact with Deep Learning
  • 144 - AI Machine Learning and Deep Learning
  • 145 - History of Machine Learning
  • 146 - Turing Machine and Turing Test
  • 147 - What is Deep Learning
  • 148 - Learning Representations From Data
  • 149 - Workflow of Machine Learning
  • 150 - Machine Learning Methods
  • 151 - Supervised Machine Learning Methods 1
  • 152 - Supervised Machine Learning Methods 2
  • 153 - Supervised Machine Learning Methods 3
  • 154 - Supervised Machine Learning Methods 4
  • 155 - Gathering data
  • 156 - Data preprocessing
  • 157 - Choosing the right algorithm and model
  • 158 - Training and testing the model
  • 159 - Evaluation

  • 21 - Artificial Neural Network
  • 160 - What Is ANN
  • 161 - Anatomy of Neural Network
  • 162 - Optimizers in Ai
  • 163 - What is TensorFlow

  • 22 - Convolutional Neural Network
  • 164 - What is CNN

  • 23 - Recurrent Neural Network and LTSM
  • 165 - Understanding RNN and LSTM Networks

  • 24 - Transfer Learning
  • 166 - What is Transfer Learning
  • 167 - What Is Data Science
  • 168 - Data literacy in Data Science
  • 169 - What is Numpy
  • 170 - Why Numpy

  • 25 - Extra
  • 171 - Artificial Intelligence with Machine Learning Deep Learning.html
  • 139,000 تومان
    بیش از یک محصول به صورت دانلودی میخواهید؟ محصول را به سبد خرید اضافه کنید.
    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.

    ایمیل شما:
    تولید کننده:
    شناسه: 38606
    حجم: 5108 مگابایت
    مدت زمان: 1378 دقیقه
    تاریخ انتشار: ۲۹ تیر ۱۴۰۳
    طراحی سایت و خدمات سئو

    139,000 تومان
    افزودن به سبد خرید