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2. Introduction To Machine Learning.mp4
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1 - Introduction to Artificial Intelligence
2 - Core Concepts in AI
7. Machine Learning Deconstructed.mp4
MP4
280.3 MB
9. The Three Pillars of Machine Learning.mp4
MP4
37.7 MB
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1 - Introduction
10 - S02L04 - Machine Learning Explained
11 - S02L05 - Generative AI and Applications
12 - Assignment Understanding AI Fundamentals
13 - 01_S03L01 - ChatGPT Getting Started and Interface
2 - 02_Meet Your Instructor Learning Approach
3 - 03_Course Roadmap_What you will learn
4 - 04_How to Use This Course_Effectively
4 - 04_How to Use This Course_Effectively.mp4
MP4
23.5 MB
5 - 05_Resources & Getting Started
5 - 05_Resources & Getting Started.mp4
MP4
24.9 MB
6 - Assignment Getting Started with Your AI Learning Journey
7 - S02L01 - What is Artificial Intelligence
7 - S02L01 - What is Artificial Intelligence.mp4
MP4
32.4 MB
8 - S02L02 - History of AI
8 - S02L02 - History of AI.mp4
MP4
30 MB
9 - S02L03 - Types of AI
9 - S02L03 - Types of AI.mp4
MP4
26.5 MB
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1 - Introduction to Machine Learning
2. What is Machine Learning.mp4
MP4
7 MB
10 - Feature Engineering
11 - Saving & Loading Models
12 - Practical ML Projects
13 - Deployment Basics
51. Deployment Workflow 2. Create API Endpoint.mp4
MP4
1.4 MB
14 - Best Practices & ML Workflow
15 - Interview Preparation
2 - Python for Machine Learning
7. Why Python for ML.mp4
MP4
5.4 MB
8. Python ML Ecosystem.mp4
MP4
17.1 MB
9. Installation & Environment Setup with practical Demo.mp4
MP4
28.4 MB
3 - ML Libraries in Python
10. ML Libraries in Python.mp4
MP4
10.6 MB
11. NumPy Basics.mp4
MP4
4.7 MB
12. Pandas Basics.mp4
MP4
3.8 MB
13. Scikit-Learn basics.mp4
MP4
3.5 MB
14. Matplotlib & Seaborn basics.mp4
MP4
3.4 MB
15. SciPy basics.mp4
MP4
2.7 MB
4 - Data Handling & Preprocessing
16. Loading & Inspecting Data.mp4
MP4
35.8 MB
17. Handling Missing Values & Feature Engineering.mp4
MP4
25.8 MB
18. Train-Test Split & Scaling Normalization.mp4
MP4
19.2 MB
5 - Exploratory Data Analysis (EDA)
19. Understanding Your Data.mp4
MP4
9.4 MB
20. Summary Statistics.mp4
MP4
10.7 MB
21. Data Visualisation Basics.mp4
MP4
19.3 MB
22. Scatter Plots & Bar Charts.mp4
MP4
13.4 MB
23. Correlation Analysis.mp4
MP4
19.1 MB
24. Distribution Plots.mp4
MP4
8.6 MB
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Introduction to Artificial Intelligence
2 - The Rise of Machine Learning
2. Artificial neural networks.mp4
MP4
8.69 MB
1. Machine learning.mp4
MP4
10.69 MB
6 - Machine Learning Algorithms
2. K-nearest neighbor.mp4
MP4
8.97 MB
3 matching files, 195 total files.
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1 - Introduction
2 - Fundamentals of Generative AI Concepts, Techniques, and Real-World Use Cases
8. Machine Learning Inference Explained From Model to Real-World Predictions.mp4
MP4
5.8 MB
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1 - Course Introduction
2 - What It Means For a Machine to Learn
4 - What Learning Means in Machine Learning.mp4
MP4
177.1 MB
3 - Linear Regression Learning From Error
11 - Overfitting and Underfitting.mp4
MP4
290.5 MB
8 - Linear Regression Predicting Numbers.mp4
MP4
202.8 MB
9 - Loss Functions Measuring Error.mp4
MP4
254.2 MB
4 - Logistic Regression Probabilities and Decisions
12 - Logistic Regression Predicting Classes.mp4
MP4
230.6 MB
13 - Probabilities and Decision Thresholds.mp4
MP4
75.5 MB
14 - Confusion Matrices and Classification Metrics.mp4
MP4
171.8 MB
5 - k-Nearest Neighbors Learning By Similarity
16 - k-Nearest Neighbors Distance-Based Learning.mp4
MP4
255.2 MB
18 - Feature Scaling and Why It Matters.mp4
MP4
141.7 MB
6 - Decision Trees Learning Rules
20 - Decision Trees Learning Rules.mp4
MP4
215.4 MB
21 - Tree Depth and Model Complexity.mp4
MP4
178.4 MB
23 - Cross-Validation Testing Model Stability.mp4
MP4
129.8 MB
7 - Random Forests Learning With Many Models
25 - Random Forests Learning With Many Models.mp4
MP4
272.4 MB
27 - Bias Vs. Variance.mp4
MP4
190.5 MB
8 - Course Conclusion
28 - Congratulations! And Next Steps.mp4
MP4
148.2 MB
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1 - Introduction to Data Science and Python
2 - Python Fundamentals for Data Science
3 - Working with Data Using Pandas
4 - Numerical Computing with NumPy
5 - Data Visualization
6 - Exploratory Data Analysis (EDA)
7 - Introduction to Statistics for Data Science
8 - Machine Learning with Scikit Learn
36. What is Machine Learning.mp4
MP4
38.7 MB
37. Supervised vs Unsupervised Learning.mp4
MP4
72.9 MB
38. ML Workflow (Prepare Train Evaluate Tune).mp4
MP4
77.2 MB
39. Regression Algorithms Linear Ridge Lasso.mp4
MP4
108.8 MB
40. Classification Algorithms Logistic Regression KNN Decision Trees.mp4
MP4
105.6 MB
41. Clustering K Means.mp4
MP4
40.2 MB
9 - Advanced Topics (Optional Bonus)
42. Introduction to Time Series Analysis.mp4
MP4
85.6 MB
43. Intro to Deep Learning with TensorFlow Keras.mp4
MP4
73.2 MB
44. Working with Big Data (Intro to PySpark).mp4
MP4
83.3 MB
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1 - Introduction To Ai Cybersecurity
2 - Generative Ai Security Automation
3 - Aipowered Threat Detection
4 - Machine Learning For Cybersecurity
10 - Machine Learning Fundamentals For Security.mp4
MP4
130.2 MB
11 - Deep Learning For Cyber Defense.mp4
MP4
115.9 MB
12 - Aibased Siem Soc Systems.mp4
MP4
84.1 MB
5 - Ethical Hacking Ai Attacks
13 - Ai For Ethical Hacking.mp4
MP4
140.7 MB
14 - Ai Security Risks Model Vulnerabilities.mp4
MP4
180.1 MB
15 - Deepfakes Voice Cloning Social Engineering.mp4
MP4
123 MB
6 - Ai Cloud Future Cybersecurity
16 - Ai In Cloud Security.mp4
MP4
136 MB
17 - Ai Agents For Cybersecurity.mp4
MP4
147.9 MB
18 - Quantum Security Future Threats.mp4
MP4
148 MB
9 matching files, 20 total files.
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1 - Quick Start
2 - Essential Web Fundamentals
3 - First Practical Project
4 - Learning to Program with Javascript
5 - Introduction to Back-End
34. Creating a Server in your machine.mp4
MP4
209 MB
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1 - Introduction
10 - Project Customer Segmentation using Clustering
11 - Project Fake News Detection using machine learning Python
12 - Project COVID19 Coronavirus Infection Probability using machine learning
13 - Miscellaneous
14 - Python Crash Course
2 - Installation and Colab
3 - Python for Data Analysis Numpy
4 - Python for Data Analysis Pandas
5 - Python for Data Visualization Matplotlib
6 - Supervised Machine Learning
29 - how to implement Logistic Regression.mp4
MP4
26.3 MB
34 - Introduction to Naive Bayes Classifier for Text Classification.mp4
MP4
12.1 MB
36 - Introduction to Decision Tree.mp4
MP4
33.4 MB
7 - UnSupervised Machine Learning
8 - Reinforcement Learning
51 - Introduction to Reinforcement Learning.mp4
MP4
38.7 MB
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1 - Introduction to Machine Learning
2 - 2 Features of Machine Learning.mp4
MP4
17.3 MB
10 - Support Vector Machines
11 - K Nearest Neighbors for Classification and Regression
12 - Decision Tree Classifier Algorithm
57 - 531 Example 2 for Decision Tree.mp4
MP4
8.8 MB
13 - Random Forest Classifier Algorithm
14 - Naive Bayes Algorithm
15 - Resources
Notebooks
16 - KMeans Clustering
2 - Types of Machine Learning
4 - 4 Difference between Supervised and Unsupervised Learning.mp4
MP4
39.2 MB
5 - 5 Algorithms in Supervised and Unsupervised Learning.mp4
MP4
12.9 MB
3 - The Machine Learning Pipeline
10 - 10 Introduction to iPython Environment.mp4
MP4
51.6 MB
6 - 6 The Machine Learning Pipeline Data Collection.mp4
MP4
43.8 MB
7 - 7 Importance of Data Prepocessing.mp4
MP4
17.9 MB
8 - 8 Importance of Feature Selection and Feature Engineering.mp4
MP4
52.5 MB
9 - 9 The Machine Learning Terminologies.mp4
MP4
36.5 MB
4 - Numpy Library
12 - 11Creating a numpy array.mp4
MP4
49.6 MB
13 - 12 Processing the numpy arrays.mp4
MP4
58.2 MB
14 - 13 Accessing Columns from Numpy Matrices.mp4
MP4
18.6 MB
15 - 14 Statistical methods in Numpy.mp4
MP4
56.2 MB
16 - 15 Matrix Operations in Numpy.mp4
MP4
53.5 MB
17 - 16 Iterating through the numpy array.mp4
MP4
24.5 MB
5 - Pandas Library
18 - 17 An Intuition on Pandas Dataframe and Series.mp4
MP4
28.1 MB
19 - 18 Using numpy arrays to create Pandas Series.mp4
MP4
28.8 MB
20 - 19 Using dictionary to create Pandas Series.mp4
MP4
26.4 MB
21 - 20 Using a scalar to create Pandas Series.mp4
MP4
10.5 MB
22 - 21 Series Processing.mp4
MP4
8.5 MB
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1 - Python Fundamentals
2 - Data Manipulation with Pandas
3 - Data Visualization with Matplotlib & Seaborn
4 - Data Analysis with NumPy
5 - Introduction to Machine Learning
23. Machine Learning Concepts.mp4
MP4
55.4 MB
24. Supervised Learning Algorithms.mp4
MP4
131.8 MB
25. Unsupervised Learning Algorithms.mp4
MP4
101.7 MB
26. Model Evaluation and Selection.mp4
MP4
132.1 MB
6 - Working with APIs and Web Data
27. Introduction to APIs.mp4
MP4
50.7 MB
28. Making API Requests.mp4
MP4
52.3 MB
29. Parsing JSON and XML Data.mp4
MP4
86.4 MB
30. Web Scraping Techniques.mp4
MP4
90.3 MB
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1 - Introduction to AI & Quantum Computing
2 - AI & Machine Learning Foundations
4. AI Fundamentals for Beginners.mp4
MP4
173.4 MB
5. Building AI Models with Python.mp4
MP4
136.2 MB
6. Deep Learning Essentials.mp4
MP4
128.7 MB
3 - Quantum Computing Foundations
10. Working with Qiskit.mp4
MP4
126.5 MB
8. Understanding Quantum Computing.mp4
MP4
122.7 MB
9. Quantum Gates & Circuits.mp4
MP4
123.7 MB
4 - Quantum Algorithms & Optimization
12. Introduction to Quantum Algorithms.mp4
MP4
137.1 MB
13. Practical Quantum Algorithms.mp4
MP4
64 MB
14. Quantum Computing for Optimization.mp4
MP4
122.2 MB
5 - Quantum Machine Learning (QML)
16. Introduction to Quantum Machine Learning.mp4
MP4
145.5 MB
17. Building Hybrid AI-Quantum Models.mp4
MP4
127.2 MB
18. Quantum Neural Networks.mp4
MP4
134.8 MB
6 - Real-World Applications of AI + Quantum
20. Quantum AI in Industry.mp4
MP4
132.7 MB
21. Quantum Security & Cryptography.mp4
MP4
168 MB
22. AI Agents & Future Intelligent Systems.mp4
MP4
133.9 MB
23. AI + Quantum Projects.mp4
MP4
67.8 MB
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1 - Introduction
2 - Introduction to Quantum Computing
3 - Fundamentals of Quantum Programming
4 - Practical Learning of Amazon Braket
23. Quantum Machine Learning on Amazon Braket.mp4
MP4
66.2 MB
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Machine Learning & Data Science with Python, Kaggle & Pandas
2. NumPy Library Introduction
1. Introduction to NumPy Library.mp4
MP4
45.3 MB
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2. Introduction To The DeepFake & Voice Cloning Mastery Machine Learning Made EASY.mp4
MP4
127.7 MB
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1 - Introduction
Logistic Regression in Python
Data Files
Others
Presentation
10 - Knearest Neighbors Classifier
11 - Understanding The Results
12 - Appendix 1 Linear Regression In Python
ML Practical task 3
ML Task 1
ML Task 2
13 - Congratulations About Your Certificate
2 - Introduction To Machine Learning
3 - Introduction To Machine Learning.mp4
MP4
145.6 MB
4 - This Is A Milestone.mp4
MP4
70.7 MB
5 - Building A Machine Learning Model.mp4
MP4
27.7 MB
3 - Basics Of Statistics
11 - Measures Of Dispersion.mp4
MP4
14.4 MB
6 - Types Of Data.mp4
MP4
20.7 MB
7 - Types Of Statistics.mp4
MP4
7.9 MB
8 - Describing Data Graphically.mp4
MP4
61.5 MB
9 - Measures Of Centers.mp4
MP4
29.8 MB
4 - Setting Up Python And Jupyter Notebook
13 - Installing Python And Anaconda.mp4
MP4
15.3 MB
14 - Opening Jupyter Notebook.mp4
MP4
54.7 MB
15 - Introduction To Jupyter.mp4
MP4
36.4 MB
16 - Arithmetic Operators In Python Python Basics.mp4
MP4
10.5 MB
17 - Strings In Python Python Basics.mp4
MP4
81.4 MB
18 - Lists Part 1.mp4
MP4
11.3 MB
19 - Lists Part 2.mp4
MP4
13.4 MB
20 - Tuples And Dictionaries.mp4
MP4
13 MB
5 - Important Python Libraries
21 - Working With Numpy Library Of Python.mp4
MP4
52.9 MB
22 - Working With Pandas Library Of Python.mp4
MP4
55.9 MB
23 - Working With Seaborn Library Of Python.mp4
MP4
61.7 MB
6 - Data Preprocessing
26 - Gathering Business Knowledge.mp4
MP4
8.7 MB
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1 - The Modern AI Landscape & Ethical Frameworks
10 - Practice Test
2 - Fundamental Principles of Machine Learning on Azure
3 - Computer Vision Workloads in Azure
4 - Natural Language Processing (NLP) & Speech
5 - Generative AI Workloads & Large Language Models (LLMs)
6 - Implementation with Microsoft AI Foundry
52. Introduction to Microsoft AI Foundry The Unified Platform.mp4
MP4
41.1 MB
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1 - Introduction To The Course
2 - Setting Up The Environment
3 - Download Resources
4 - Zeppelin Basics
5 - Zeppelin With Apache Spark
6 - Machine Learning Project
35 - Understanding Spark Imports For Ml.mp4
MP4
14.5 MB
36 - Loading Source Data In Spark.mp4
MP4
23.1 MB
37 - Preparing Training Data.mp4
MP4
24.9 MB
38 - Understanding Stringindexer In Spark.mp4
MP4
15.3 MB
39 - Defining The Pipeline In Spark Mllib.mp4
MP4
43.9 MB
40 - Split The Data.mp4
MP4
12.8 MB
41 - Using Vectorassembler To Prepare Training Data.mp4
MP4
59.7 MB
42 - Train A Regression Model In Spark.mp4
MP4
47.9 MB
43 - Prepare The Testing Data.mp4
MP4
25.6 MB
44 - Testing The Regression Model In Spark.mp4
MP4
51.9 MB
45 - Evaluating The Regression Model In Spark.mp4
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20 MB
46 - Evaluating Model Performance Using Rmse.mp4
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40.7 MB
7 - Introduction
47 - Introduction.mp4
MP4
31.5 MB
8 - Download Resources
SourceCode
9 - Project Begins
49 - Introduction To Spark.mp4
MP4
42.6 MB
50 - Old Free Account Creation In Databricks.mp4
MP4
7.7 MB
51 - New Free Account Creation In Databricks.mp4
MP4
8.7 MB
52 - Tips To Improve Your Course Taking Experience.mp4
MP4
3 MB
53 - Provisioning A Spark Cluster.mp4
MP4
10 MB
54 - Introduction To Machine Learning.mp4
MP4
35 MB
55 - Basics About Notebooks.mp4
MP4
30.7 MB
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Data Science Real World Projects in Python
[TutsNode.com] - Data Science Real World Projects in Python
2. Project 1-- Predict Fare of Airlines Tickets using Machine Learning
1. Introduction to Business Problem & Dataset.mp4
MP4
21.66 MB
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Machine Learning Made Easy - Beginner to Advanced using R
Machine Learning Made Easy - Beginner to Advanced using R
1. Introduction to R
2. R Environment.mp4
MP4
9.64 MB
2. Data Handling in R
1. Introduction to Data Handling.mp4
MP4
2.63 MB
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1 - Introduction to AI in Market Strategy
2 - Core AI Technologies and Tools
3. Understanding AI, Machine Learning, and Data Analytics.mp4
MP4
320.9 MB
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2 - Introduction to Machine Learning.mp4
MP4
55.7 MB
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[FreeCoursesOnline.Me] UDACITY - Machine Learning Engineer Nanodegree v4.0.0
Part 03-Module 01-Lesson 01_Introduction to Deployment
04. Machine Learning Workflow - Part 2 Details-ku_96X6TZas.mp4
MP4
13.73 MB
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1 - Introduction
2 - Machine Learning Paradigms & Bias-Variance Bounds
3 - Deep Neural Networks & Gradient Propagation Models
16 - Introduction to Alignment Drift.mp4
MP4
57 MB
4 - Natural Language Processing & Embedding Geometries
19 - Introduction to Reward Modeling.mp4
MP4
57.9 MB
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1 - Introduction and Outline
10 - Extra Help With Python Coding for Beginners (FAQ by Student Request)
11 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)
12 - Appendix FAQ Finale
2 - The High-Level Picture
3 - Bayes Rule and Probability Review
4 - Traditional A B Testing
5 - Bayesian A B Testing
6 - Bayesian A B Testing Extension
7 - Practice Makes Perfect
65. Intro to Exercises on Conjugate Priors.mp4
MP4
16.9 MB
8 - Appendix FAQ Intro
9 - Setting Up Your Environment (FAQ by Student Request)
71. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
MP4
192.3 MB
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1 - Welcome to Introduction to Databricks
2 - Databricks Core Components
3 - Databricks Architecture
4 - Databricks in Action
5 - Machine Learning - Regression Analysis
23. Data Science Core Concepts.mp4
MP4
11.8 MB
24. ML Regression Data Prep.mp4
MP4
23.8 MB
25. Converting SQL table to Pyspark table.mp4
MP4
53.9 MB
26. Training Regression Model on Bitcoin Prices.mp4
MP4
29.3 MB
27. Displaying Bitcoin Prediction Price in Pan.mp4
MP4
34.3 MB
28. Importing Python Notebook into Databricks.mp4
MP4
8.3 MB
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2 - Introduction to AI and Machine Learning for Handyman Work.mp4
MP4
51.2 MB
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[FreeCoursesOnline.Me] UDACITY - Machine Learning Scholarship Program for Microsoft Azure
Part 01-Module 01-Lesson 01_Welcome to Introduction to Machine Learning on Azure
04. Microsoft Azure PROMO (2)-hwtrw64xQmQ.mp4
MP4
11.81 MB
Part 01-Module 01-Lesson 02_Introduction to Machine Learning
28. 1 23 11983 Udacity ML Course Lesson1 FINAL V2-2_JMdUc0D0c.mp4
MP4
10.8 MB
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1 - Introduction to ML CFD Integration
2 - Fundamentals of Fluid Mechanics for ML Models
3 - Overview of Machine Learning in Physics Based Systems
12. Data driven vs Physics informed approches.mp4
MP4
55.5 MB
13. Neural network architectures for physical systems.mp4
MP4
41.2 MB
14. Proper orthogonal decomposition (POD) and reduced order models (ROMs).mp4
MP4
46.5 MB
15. Embedding physical constraints in ML models.mp4
MP4
72.7 MB
16. Case studies turbulence modelling heat transfer prediction.mp4
MP4
49.5 MB
4 - Synthetic Data Generation for ML CFD
17. Reduced physics CFD simulations.mp4
MP4
53.4 MB
18. Dataset design geometries flow regimes boundary diversity.mp4
MP4
65.2 MB
19. Voxelization of geometric inputs (256³ resolution).mp4
MP4
60.7 MB
20. Ensuring physical consistency of synthetic data.mp4
MP4
58.5 MB
21. Data augmention strategies and bias mitigation.mp4
MP4
59.8 MB
22. Statical verification of dataset.mp4
MP4
59.9 MB
5 - Convolutional Neural Networks for CFD Prediction
23. CNN encoder decoder architectures.mp4
MP4
33.3 MB
24. Convolution in volumetric data.mp4
MP4
51.1 MB
25. Loss functions incorporating physical constraints.mp4
MP4
52.2 MB
26. Training workflow.mp4
MP4
23.7 MB
27. Hyperparameter optimization.mp4
MP4
23.2 MB
28. Avoiding overfitting and promoting generalization.mp4
MP4
44.6 MB
29. Implementation best practices.mp4
MP4
57.2 MB
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2 -Introduction to AI and Machine Learning for Electrician Work.mp4
MP4
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Data Science Practical Automated Machine Learning(Auto ML)
[TutsNode.com] - Data Science Practical Automated Machine Learning(Auto ML)
2. Introduction to AutoML
3. Introduction to Auto Keras.mp4
MP4
31.06 MB
1. Introduction to Auto Sklearn.mp4
MP4
24.98 MB
2. Introduction to TPOT.mp4
MP4
14.29 MB
6. TPOT Models Part 2
1. Introduction to Red wine quality classification.mp4
MP4
28.81 MB
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01 - Introduction
02 - 1. An Overview of Full-Stack Deep Learning
03 - 2. MLOps with MLflow
04 - 3. Model Training and Evaluation Using MLflow
05 - 4. Hyperparameter Tuning with Optuna
06 - 5. Model Deployment and Predictions
02 - Workaround to get model artifacts on local machine.mp4
MP4
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1 - Pandas
10 - Lets apply what we learned Machine Learning Project Classification
11 - Lets apply what we learned Machine Learning Project Regression
12 - Bonus Section
2 - Numpy
5 - Numpy Introduction to Arrays.mp4
MP4
12.7 MB
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1 - Introduction to Machine Learning
2 - What is Machine Learning.mp4
MP4
34.7 MB
2 - Data and Feature Engineering
6 - Understanding Data in Machine Learning.mp4
MP4
27.2 MB
7 - Data Preprocessing Concepts.mp4
MP4
86.3 MB
8 - Feature Engineering and Feature Selection.mp4
MP4
43.1 MB
3 - Supervised Learning Core Concepts
10 - Regression Algorithms Concepts Only.mp4
MP4
19.3 MB
11 - Classification Algorithms Concepts Only.mp4
MP4
40.9 MB
12 - Evaluating Supervised Models.mp4
MP4
42.7 MB
9 - Introduction to Supervised Learning.mp4
MP4
30.4 MB
4 - Unsupervised Learning Discovering Hidden Patterns
13 - Introduction to Unsupervised Learning.mp4
MP4
51 MB
14 - Clustering Techniques.mp4
MP4
28.1 MB
15 - Dimensionality Reduction.mp4
MP4
33.6 MB
5 - Reinforcement Learning Conceptual Overview
16 - Introduction to Reinforcement Learning.mp4
MP4
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17 - Core Concepts in RL.mp4
MP4
24.9 MB
18 - Popular RL Algorithms Conceptual.mp4
MP4
41.9 MB
6 - Model Evaluation and Improvement
19 - Train Validation and Test Splits.mp4
MP4
34.7 MB
20 - CrossValidation Concept.mp4
MP4
19.2 MB
21 - Model Optimization and Hyperparameter Tuning.mp4
MP4
49.2 MB
22 - Bias and Variance Revisited.mp4
MP4
48.4 MB
7 - Deep Learning Conceptual Foundations
23 - What is Deep Learning.mp4
MP4
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24 - Artificial Neural Networks The Concept.mp4
MP4
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2 - Introduction to Machine Learning.mp4
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College Level Neural Nets [I] - Basic Nets Math & Practice!
[TutsNode.com] - College Level Neural Nets [I] - Basic Nets Math & Practice!
1. Introduction To Machine Learning
2. Introduction To Machine Learning.mp4
MP4
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[FreeAllCourse.Com] Udemy - Python for Data Science and Machine Learning Bootcamp
4. Python Crash Course
2. Introduction to Python Crash Course.mp4
MP4
3.04 MB
5. Python for Data Analysis - NumPy
2. Introduction to Numpy.mp4
MP4
4.73 MB
6. Python for Data Analysis - Pandas
2. Introduction to Pandas.mp4
MP4
3.53 MB
8. Python for Data Visualization - Matplotlib
2. Introduction to Matplotlib.mp4
MP4
16.34 MB
14. Introduction to Machine Learning
2. Welcome to the Machine Learning Section!.mp4
MP4
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10 Python Courses For Beginners 2020 [UdemyLibrary.com]
Machine Learning Crash Course for Beginners using Python [UdemyLibrary.com]
1. Introduction to the Course
2. Focus of the Course.mp4
MP4
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11. Deep Learning Overview
2. Introduction to Convolutional Neural Networks (CNN).mp4
MP4
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[Tutorialsplanet.NET] Udemy - Python for Data Science and Machine Learning Bootcamp
4. Python Crash Course
2. Introduction to Python Crash Course.mp4
MP4
2.66 MB
5. Python for Data Analysis - NumPy
2. Introduction to Numpy.mp4
MP4
4.16 MB
6. Python for Data Analysis - Pandas
2. Introduction to Pandas.mp4
MP4
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8. Python for Data Visualization - Matplotlib
2. Introduction to Matplotlib.mp4
MP4
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2 - Introduction to AI and Machine Learning for Plumber Work.mp4
MP4
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[CourseClub.Me] UDACITY - Machine Learning Scholarship Program for Microsoft Azure
Part 01-Module 01-Lesson 01_Welcome to Introduction to Machine Learning on Azure
04. Microsoft Azure PROMO (2)-hwtrw64xQmQ.mp4
MP4
11.81 MB
Part 01-Module 01-Lesson 02_Introduction to Machine Learning
28. 1 23 11983 Udacity ML Course Lesson1 FINAL V2-2_JMdUc0D0c.mp4
MP4
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[FreeTutorials.Us] Master Computer Vision OpenCV4 in Python with Deep Learning
13. BONUS - Deep Learning Computer Vision 2 - Introduction to Neural Networks
2. Machine Learning Overview.mp4
MP4
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1 - Introduction
2 - Domain 1 - Basic AI Concepts Related to Cybersecurity ( 17%)
5. Machine Learning - What is it Risks & Mitigations.mp4
MP4
68 MB
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[FreeCoursesOnline.Me] PacktPub - Master Deep Learning with TensorFlow 2.0 in Python [2019] [Video]
02.Introduction to neural networks
0203.Types of machine learning.mp4
MP4
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1 - Introduction
2 - Module 1 Introduction to Generative AI for Software Testing
2 - AI Spectrum Symbolic AI, Classical Machine Learning, Deep Learning & GenAI.mp4
MP4
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2. Introduction to Machine Learning Part Two.mp4
MP4
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2021 Python for Data Science & Machine Learning from A-Z
[TutsNode.com] - 2021 Python for Data Science & Machine Learning from A-Z
7. Pandas Data Analysis
2. Introduction to Pandas Continued.mp4
MP4
71.1 MB
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Python for Data Science
[TutsNode.com] - Python for Data Science
1. Introduction to Machine Learning and It’s Technologies
2. Segment - 03.mp4
MP4
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1 - Introduction to AI in Insurance (InsurTech Overview)
10 - Insurance AI Architecture & Implementation Strategy
11 - Capstone Case Studies & Future of InsurTech
2 - Foundations – Insurance Data, AI & Machine Learning Basics
2. Foundations – Insurance Data, AI & Machine Learning Basics.mp4
MP4
83.6 MB
3 - AI-Driven Underwriting Automation
3. AI-Driven Underwriting Automation.mp4
MP4
111.2 MB
4 - Claims Processing Automation Using Computer Vision & NLP
4. Claims Processing Automation Using Computer Vision & NLP.mp4
MP4
132.1 MB
5 - Fraud Detection in Insurance Claims Using AI
5. Fraud Detection in Insurance Claims Using AI.mp4
MP4
168.2 MB
6 - Dynamic Pricing Models Using Real-Time Data
6. Dynamic Pricing Models Using Real-Time Data.mp4
MP4
136.2 MB
7 - Usage-Based Insurance (UBI) Powered by IoT & AI
7. Usage-Based Insurance (UBI) Powered by IoT & AI.mp4
MP4
131.9 MB
8 - AI for Customer Experience & Personalization
8. AI for Customer Experience & Personalization.mp4
MP4
118.8 MB
9 - AI Governance, Ethics, Bias & Regulation in Insurance
9. AI Governance, Ethics, Bias & Regulation in Insurance.mp4
MP4
126.9 MB
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