Udemy AI Programming in C Sharp-Beginner to Expert

Files Included :
1 -Introduction (82.1 MB)
2 -Introduction to Artificial Intelligence (AI) (26.37 MB)
3 -Why learn to code AI (20.88 MB)
4 -What will we build in this course (87.34 MB)
5 -Download and Install Visual Studio Code with C# Dev Kit (Mac) (23.53 MB)
6 -Download and Install Visual Studio Code with C# Dev Kit (Windows) (8.35 MB)
1 -Section Introduction (6.62 MB)
10 -Section Summary (4.89 MB)
2 -Forecasting (36.09 MB)
3 -Sneak Peek at Finished Project (12.7 MB)
4 -Creating the Project (11.66 MB)
5 -Setting up the Data (15.22 MB)
6 -Loading the Data (12.3 MB)
7 -Training the Model (17.39 MB)
8 -Evaluating and Testing the Model (27.5 MB)
9 -Answers & Explanations to Quiz Questions (13.58 MB)
1 -Section Introduction (6.87 MB)
10 -Section Summary (4.85 MB)
2 -Recommendation (48 MB)
3 -Sneak Peek at Finished Project (11.52 MB)
4 -Creating the Project (6.08 MB)
5 -Preprocessing the Data (53.11 MB)
6 -Loading the Data (31.32 MB)
7 -Training the Model (46.08 MB)
8 -Evaluating and Testing the Model (41.53 MB)
9 -Answers & Explanations to Quiz Questions (15.89 MB)
1 -Section Introduction (7.12 MB)
10 -Section Summary (6.52 MB)
2 -Sentiment Analysis (31.32 MB)
3 -Sneak Peek at Finished Project (22.78 MB)
4 -Creating the Project (11.12 MB)
5 -Preprocessing the Data (31.92 MB)
6 -Loading the Data (16.5 MB)
7 -Training the Model (15.55 MB)
8 -Evaluating and Testing the Model (25.95 MB)
9 -Answers & Explanations to Quiz Questions (18.47 MB)
1 -Section Introduction (7.28 MB)
10 -Section Summary (6.16 MB)
2 -Anomaly Detection (18.14 MB)
3 -Sneak Peek at Finished Project (41.61 MB)
4 -Creating the Project (12.32 MB)
5 -Preprocessing the Data (20.21 MB)
6 -Loading the Data (14.74 MB)
7 -Training the Model (15.17 MB)
8 -Evaluating and Testing the Model (32.39 MB)
9 -Answers & Explanations to Quiz Questions (13.09 MB)
1 -Section Introduction (6.8 MB)
10 -Section Summary (5.62 MB)
2 -Text Generation (24.63 MB)
3 -Sneak Peek at Finished Project (24.14 MB)
4 -Creating the Project (12.78 MB)
5 -Preprocessing the Data (9.79 MB)
6 -Loading the Data (10.87 MB)
7 -Training the Model (28.54 MB)
8 -Evaluating and Testing the Model (48.24 MB)
9 -Answers & Explanations to Quiz Questions (18.93 MB)
1 -Section Introduction (7.37 MB)
10 -Section Summary (6.06 MB)
2 -Time Series Analysis (19.76 MB)
3 -Sneak Peek at Finished Project (8.43 MB)
4 -Creating the Project (12.48 MB)
5 -Loading the Data (18.33 MB)
6 -Preprocessing the Data (17.86 MB)
7 -Training the Model (15.47 MB)
8 -Evaluating and Testing the Model (84.45 MB)
9 -Answers & Explanations to Quiz Questions (13.11 MB)
1 -Section Introduction (6.46 MB)
2 -Clustering (22.55 MB)
3 -Sneak Peek at Finished Project (8.67 MB)
4 -Creating the Project (13.49 MB)
5 -Loading the Data (21.82 MB)
6 -Training the Model (12.58 MB)
7 -Evaluating and Testing the Model (19.63 MB)
8 -Answers & Explanations to Quiz Questions (11.13 MB)
9 -Section Summary (5.73 MB)
1 -Section Introduction (7.36 MB)
10 -Section Summary (5.99 MB)
2 -Reinforcement Learning (31.33 MB)
3 -Sneak Peek at Finished Project (5.94 MB)
4 -Creating the Project (13.44 MB)
5 -Setting Up the Environment (44.44 MB)
6 -Defining the Q-Learning Algorithm (50.37 MB)
7 -Implementing the Training Process (40.53 MB)
8 -Testing the trained agent (25.03 MB)
9 -Answers & Explanations to Quiz Questions (13.75 MB)
1 -Section Introduction (7.9 MB)
2 -Reading and Writing Data to Files (66.57 MB)
3 -Data Preprocessing Techniques (71.59 MB)
4 -Exploratory Data Analysis (EDA) (79.78 MB)
5 -Feature Engineering (63.92 MB)
6 -Data Integration and Aggregation (47.88 MB)
7 -Answers & Explanations to Quiz Questions (14.4 MB)
8 -Section Summary (6.23 MB)
1 -Section Introduction (14.12 MB)
10 -Eigenvalue Decomposition and Singular Value Decomposition (29.61 MB)
11 -Multivariate Data Analysis and Dimensionality Reduction (75.23 MB)
12 -Answers & Explanations to Quiz Questions (15.19 MB)
13 -Section Summary (12.75 MB)
2 -Introduction to Math NET Numerics (34.19 MB)
3 -Statistical Analysis with Math NET Numerics (30.87 MB)
4 -Linear Algebra Operations with Math NET Numerics (32.4 MB)
5 -Numerical Integration and Differentiation (23.35 MB)
6 -Solving Linear Equations and Systems (37.77 MB)
7 -Curve Fitting and Interpolation Techniques (34.82 MB)
8 -Optimization Methods in Math NET Numerics (22.74 MB)
9 -Sparse Matrices and Compressed Storage Formats (30.03 MB)
1 -Section Introduction (7.81 MB)
10 -Generative AI (33.53 MB)
11 -Computer Vision (34.51 MB)
12 -Answers & Explanations to Quiz Questions (33.31 MB)
13 -Section Summary (6.19 MB)
2 -Types of AI (30.87 MB)
3 -Neural Networks (19.53 MB)
4 -Machine Learning (18.7 MB)
5 -Q-Learning (22.4 MB)
6 -Deep Q-Learning (27.61 MB)
7 -Deep Convolutional Q-Learning (34.71 MB)
8 -Asynchronous Advantage Actor-Critic (A3C) (38.29 MB)
9 -Large Language Models (LLMs) (36.91 MB)
1 -Section Introduction (9.91 MB)
10 -Answers & Explanations to Quiz Questions (14.5 MB)
11 -Section Summary (8.72 MB)
2 -Introduction to NumSharp (43.31 MB)
3 -Working with Arrays in NumSharp (50.77 MB)
4 -Basic Mathematical Operations with NumSharp (50.03 MB)
5 -Indexing and Slicing Arrays in NumSharp (38.33 MB)
6 -Linear Algebra Operations with NumSharp (15.77 MB)
7 -Statistical Analysis with NumSharp (26.5 MB)
8 -Array Broadcasting and Universal Functions (ufuncs) (34.97 MB)
9 -Advanced Array Manipulation Techniques (20.64 MB)
1 -Section Introduction (10.82 MB)
10 -Seasonality and Trend Analysis in Time Series Data (42.81 MB)
11 -Stationarity Testing with Deedle (21.11 MB)
12 -Integration with ML NET for Time Series Prediction (60.54 MB)
13 -Answers & Explanations to Quiz Questions (20.22 MB)
14 -Section Summary (9.93 MB)
2 -Introduction to Deedle (26.07 MB)
3 -Loading and Manipulating Time Series Data with Deedle (28.02 MB)
4 -Basic Time Series Operations with Deedle (27.2 MB)
5 -Resampling and Aggregating Time Series Data (31.2 MB)
6 -Time Series Indexing and Slicing in Deedle (34.47 MB)
7 -Missing Data Handling in Time Series Analysis with Deedle (31.13 MB)
8 -Rolling Windows and Moving Averages (16.67 MB)
9 -Time Series Visualization with Deedle (30.97 MB)
1 -Section Introduction (12.37 MB)
10 -Ensemble Learning and Random Forests in Accord NET (40.72 MB)
11 -Support Vector Machines (SVM) with Accord NET (27.45 MB)
12 -Neural Networks and Deep Learning with Accord NET (27.73 MB)
13 -Answers & Explanations to Quiz Questions (37.56 MB)
14 -Section Summary (11.03 MB)
2 -Introduction to Accord NET (20.77 MB)
3 -Loading and Preprocessing Data with Accord NET (32.93 MB)
4 -Exploratory Data Analysis (EDA) with Accord NET (49.62 MB)
5 -Basic Statistical Analysis with Accord NET (72.5 MB)
6 -Classification Algorithms in Accord NET (33.97 MB)
7 -Regression Techniques with Accord NET (32.44 MB)
8 -Clustering Methods in Accord NET (31.15 MB)
9 -Dimensionality Reduction Techniques (27.43 MB)
1 -Section Introduction (19.51 MB)
10 -Obstacle Avoidance and Pathfinding Strategies for Mario (50.05 MB)
11 -Dynamic Difficulty Adjustment Adaptive Algorithms (27.24 MB)
12 -UI Design Algorithm Selection & Configuration (98.71 MB)
13 -Evaluating Mario's Performance Metrics & Visualization (43.7 MB)
14 -Hyperparameter Fine-Tuning Optimization Techniques (45.84 MB)
15 -Handling Sparse Rewards Reward Shaping & Function Approximation (23.53 MB)
16 -Exploration-Exploitation Strategies Epsilon-Greedy & Softmax (54.71 MB)
17 -Debugging & Troubleshooting ML Agents (18.26 MB)
18 -Model Interpretability Understanding Agent Behavior (32.53 MB)
19 -Continuous & Transfer Learning Strategies (74.44 MB)
2 -Download and Install Unity (19.43 MB)
20 -Deploying the Trained Mario Agent in Unity (30.07 MB)
21 -Answers & Explanations to Quiz Questions (18.14 MB)
22 -Section Summary (18.34 MB)
3 -What are ML Agents (18.59 MB)
4 -Importing the ML Agents Unity Package (10.31 MB)
5 -ML Agents in Unity Building a Mario Agent (62.66 MB)
6 -Setting Up Mario's Environment Level Design & Initialization (130.78 MB)
7 -Observations & Actions Input & Output Spaces (12.34 MB)
8 -Coin Collection Rewards & Greedy Algorithm (116.98 MB)
9 -Advanced Coin Collection Q-Learning & Policy Gradient (82.18 MB)
1 -Section Introduction (10.25 MB)
10 -Distributed Training Scaling Model Training (17.73 MB)
11 -Answers & Explanations to Quiz Questions (28.76 MB)
12 -Section Summary (9.75 MB)
2 -Model Performance Evaluation Metrics & Techniques (20.57 MB)
3 -Hyperparameter Tuning Strategies for Better Performance (19.17 MB)
4 -Grid vs Random Search Hyperparameter Optimization (25.56 MB)
5 -Bayesian Optimization for Hyperparameter Tuning (26.62 MB)
6 -Automated Machine Learning (AutoML) for Model Selection (27.67 MB)
7 -Model Interpretability Techniques (26.41 MB)
8 -Pruning Models for Efficiency (21.2 MB)
9 -Quantization & Compression for Model Optimization (25.23 MB)
1 -Section Introduction (18.58 MB)
10 -Error Handling Exception Handling and Try-Catch Blocks (21.05 MB)
11 -Asynchronous Programming with asyncawait (23.35 MB)
12 -LINQ Fundamentals Querying Collections (20.15 MB)
13 -LINQ Operators Filtering, Sorting, and Grouping Data (21.83 MB)
14 -Delegates and Events Understanding Event-Driven Programming (44.12 MB)
15 -Reflection and Attributes in C# Accessing Type Information (52.5 MB)
16 -File IO Operations Reading and Writing Files (37.64 MB)
17 -Working with Streams Stream-Based IO Operations (67.66 MB)
18 -Best Practices and Coding Standards for C# Programming (19.28 MB)
19 -Answers & Explanations to Quiz Questions (15.95 MB)
2 -Introduction to C# Programming Language (25.04 MB)
20 -Section Summary (17.99 MB)
3 -Understanding Variables and Data Types in C# (26.34 MB)
4 -Control Flow If Statements and Switch Statements (23.11 MB)
5 -Looping Constructs For, While, and Do-While Loops (19.3 MB)
6 -Introduction to Object-Oriented Programming (OOP) in C# (25.85 MB)
7 -Encapsulation Access Modifiers and Data Hiding (22.56 MB)
8 -Working with Collections Arrays, Lists, and Dictionaries (18.65 MB)
9 -Introduction to Generics in C# (26.52 MB)
1 -Section Introduction (11.88 MB)
10 -Eigenvalues and Eigenvectors (26.89 MB)
11 -Matrix Rank and Null Space (29.2 MB)
12 -Singular Value Decomposition (SVD) (39.72 MB)
13 -Least Squares Estimation (25.77 MB)
14 -Linear Transformations and Kernel (31.48 MB)
15 -Principal Component Analysis (PCA) and Dimensionality Reduction (28.73 MB)
16 -Applications of Linear Algebra in Machine Learning (28.7 MB)
17 -Answers & Explanations to Quiz Questions (9.7 MB)
18 -Section Summary (10.23 MB)
2 -Introduction to Linear Algebra (53.07 MB)
3 -Matrices and Operations (55.5 MB)
4 -Solving Linear Systems (79.81 MB)
5 -Vector Spaces and Subspaces (25.53 MB)
6 -Linear Independence and Span (21.78 MB)
7 -Orthogonality and Orthogonal Matrices (32.12 MB)
8 -Matrix Transformations and Geometry (29.51 MB)
9 -Inner Products and Norms (20.8 MB)
1 -Course Summary & Wrap-Up (63.49 MB)
2 -Bonus Lecture (21.77 MB)
1 -Section Introduction (9.27 MB)
10 -Section Summary (7.84 MB)
2 -What is ChatGPT (31.01 MB)
3 -Writing More Effective Generative AI Prompts (16.78 MB)
4 -ChatGPT Project 1 Using ChatGPT to Brainstorm Ideas (27.64 MB)
5 -ChatGPT Project 2 Using ChatGPT to Write a First Draft (23.72 MB)
6 -ChatGPT Project 3 Using ChatGPT to Create a Workout Plan (13.89 MB)
7 -ChatGPT Project 4 Using ChatGPT to Summarize a Book (21.1 MB)
8 -ChatGPT Project 5 Using ChatGPT to Write Code (11.22 MB)
9 -Answers & Explanations to Quiz Questions (8.5 MB)
1 -Section Introduction (5.67 MB)
2 -What is TorchSharp (9.92 MB)
3 -Creating the Maze (The Environment) (13.46 MB)
4 -Actions & Rewards (22.55 MB)
5 -Training the Model (68.94 MB)
6 -Final Result (66.84 MB)
7 -Answers & Explanations to Quiz Questions (6.37 MB)
8 -Section Summary (5.24 MB)
1 -Section Introduction (8.99 MB)
10 -Coding a Neural Network The Transpose Function (21.9 MB)
11 -Coding a Neural Network Testing our Code (50.18 MB)
12 -Real World Applications of Neural Networks (28.54 MB)
13 -Answers & Explanations to Quiz Questions (11.25 MB)
14 -Section Summary (7.87 MB)
2 -What is a Neural Network (14.54 MB)
3 -Neural Network Architecture (63.12 MB)
4 -Sneak Peek at Finished Project (8.65 MB)
5 -Coding a Neural Network The Neural Network Class (19.29 MB)
6 -Coding a Neural Network The Activate Function (32.97 MB)
7 -Coding a Neural Network The Train Function (23.83 MB)
8 -Coding a Neural Network The Dot Product Function (21.86 MB)
9 -Coding a Neural Network The Perform Operation Function (21.68 MB)
1 -Section Introduction (8.64 MB)
10 -Answers & Explanations to Quiz Questions (25.66 MB)
11 -Section Summary (7.04 MB)
2 -What is ML NET (20.37 MB)
3 -Setting up ML NET (12.4 MB)
4 -Introduction to Machine Learning with ML NET (54.79 MB)
5 -Data Preparation and Loading in ML NET (24.32 MB)
6 -Feature Engineering in ML NET (43.91 MB)
7 -Model Selection and Evaluation in ML NET (90.5 MB)
8 -Training and Tuning Models in ML NET (24.89 MB)
9 -Model Deployment and Integration with ML NET (21.52 MB)
1 -Section Introduction (7.13 MB)
10 -Section Summary (5.77 MB)
2 -Classification (49.68 MB)
3 -Sneak Peek at Finished Project (13.24 MB)
4 -Creating the Project (13.13 MB)
5 -Setting up the Data (13.29 MB)
6 -Loading the Data (47.09 MB)
7 -Training the Model (34.52 MB)
8 -Evaluating and Testing the Model (46.13 MB)
9 -Answers & Explanations to Quiz Questions (23.03 MB)
1 -Section Introduction (7.49 MB)
10 -Section Summary (5.93 MB)
2 -Image Classification (13.95 MB)
3 -Sneak Peek at Finished Project (17.43 MB)
4 -Creating the Project (10.36 MB)
5 -Data (7.49 MB)
5 -Setting up the Data (8.98 MB)
6 -Loading the Data (63.07 MB)
7 -Training the Model (32 MB)
8 -Evaluating and Testing the Model (50.47 MB)
9 -Answers & Explanations to Quiz Questions (13.92 MB)
1 -Section Introduction (6.38 MB)
10 -Section Summary (5.38 MB)
2 -Regression (47.98 MB)
3 -Sneak Peek at Finished Project (17.08 MB)
4 -Creating the Project (11.03 MB)
5 -Preprocessing and Loading the Data (40.59 MB)
6 -Training the Model (14.23 MB)
7 -Evaluating the Model (9.64 MB)
8 -Testing the Model (18.07 MB)
9 -Answers & Explanations to Quiz Questions (17.81 MB)]
Screenshot
[Image: wkuQHxRH_o.jpg]