8.74 GB | 28min 11s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English
Files Included :
1 -Overview.mp4 (33.63 MB)
2 -What is Machine Learning.mp4 (92.87 MB)
3 -Types of Machine Learning.mp4 (66.47 MB)
4 -Machine Learning Pipeline.mp4 (33.33 MB)
5 -Key Concepts Features, Labels, Training, and Testing.mp4 (82.95 MB)
6 -Tools and Libraries for Machine Learning in Python.mp4 (46.65 MB)
1 -Essential Python Libraries for AI.mp4 (201.33 MB)
2 -Data Management Techniques.mp4 (236.9 MB)
1 -NLP Fundamentals.mp4 (136.35 MB)
2 -Working with Word Embeddings.mp4 (272.39 MB)
3 -NLP Applications.mp4 (202.6 MB)
4 -Project - Build a basic text classification model.mp4 (71.94 MB)
1 -Basics of Image Processing.mp4 (266.19 MB)
2 -Object Recognition and Feature Extraction.mp4 (122.25 MB)
3 -Applications in Vision.mp4 (258.56 MB)
4 -Project - Create a pipeline for image classification.mp4 (146.33 MB)
1 -Fundamentals of Search.mp4 (293.46 MB)
2 -Optimization Techniques.mp4 (220.51 MB)
3 -Applications of Search in AI.mp4 (166.39 MB)
4 -Project - Implement A search.mp4 (116.87 MB)
1 -Introduction to Reinforcement Learning.mp4 (148.56 MB)
2 -Q-Learning Basics.mp4 (222.19 MB)
1 -Introduction to Generative AI.mp4 (117.62 MB)
2 -Working with Autoencoders.mp4 (174.66 MB)
3 -Applications of Generative AI.mp4 (65.06 MB)
4 -Project - Generate realistic text using an AI-based language model.mp4 (133.5 MB)
1 -Exploratory Data Analysis.mp4 (88.63 MB)
2 -Data Cleaning Handling missing data.mp4 (185.58 MB)
3 -Data Cleaning Removing duplicates and fixing inconsistencies.mp4 (83.11 MB)
4 -Feature Scaling.mp4 (152.86 MB)
5 -Data Transformation and Encoding.mp4 (115.04 MB)
6 -Splitting Data TrainTest Split.mp4 (147.22 MB)
7 -Practical Implementation.mp4 (121.62 MB)
1 -Introduction to Linear Regression.mp4 (95.01 MB)
2 -Implementing Linear Regression in Python.mp4 (69.31 MB)
3 -Polynomial Regression.mp4 (109.89 MB)
4 -Ridge, Lasso, and Elastic Net Regression.mp4 (166.54 MB)
5 -Project - Predicting Housing Prices.mp4 (190.84 MB)
1 -Understanding Logistic Regression.mp4 (216.07 MB)
2 -Implementing Logistic Regression in Python.mp4 (202.72 MB)
3 -Decision Trees.mp4 (159.51 MB)
4 -k-Nearest Neighbors (k-NN).mp4 (119.44 MB)
5 -Support Vector Machines (SVM).mp4 (117.97 MB)
6 -Project - Comparing Classification Models.mp4 (97.06 MB)
1 -Introduction to Ensemble Learning.mp4 (115.66 MB)
2 -Random Forest.mp4 (171.75 MB)
3 -Gradient Boosting Algorithms.mp4 (155.52 MB)
4 -Project - Credit card fraud detection using ensemble methods.mp4 (217.16 MB)
1 -K-Means Clustering.mp4 (196.82 MB)
2 -Hierarchical Clustering.mp4 (131 MB)
3 -Density-Based Clustering.mp4 (130.66 MB)
4 -Project - Customer Segmentation Using Clustering Algorithms.mp4 (131.85 MB)
1 -Principal Component Analysis (PCA).mp4 (138.6 MB)
2 -t-SNE (t-Distributed Stochastic Neighbor Embedding).mp4 (179.02 MB)
3 -Autoencoders.mp4 (243.29 MB)
4 -Project - Visualizing Wine Data Using PCA and t-SNE.mp4 (98.89 MB)
1 -Introduction to Association Rules - Market Basket Analysis.mp4 (139.64 MB)
2 -Apriori Algorithm.mp4 (97.58 MB)
3 -FP-Growth Algorithm.mp4 (123.5 MB)
4 -Project - Market Basket Analysis for E-commerce Data.mp4 (63.12 MB)
1 -Course Overview.mp4 (26.21 MB)
2 -What is Artificial Intelligence.mp4 (119.91 MB)
3 -AI vs ML vs DL.mp4 (42.76 MB)
4 -Core Components of AI.mp4 (42.13 MB)
2 -What is Machine Learning.mp4 (92.87 MB)
3 -Types of Machine Learning.mp4 (66.47 MB)
4 -Machine Learning Pipeline.mp4 (33.33 MB)
5 -Key Concepts Features, Labels, Training, and Testing.mp4 (82.95 MB)
6 -Tools and Libraries for Machine Learning in Python.mp4 (46.65 MB)
1 -Essential Python Libraries for AI.mp4 (201.33 MB)
2 -Data Management Techniques.mp4 (236.9 MB)
1 -NLP Fundamentals.mp4 (136.35 MB)
2 -Working with Word Embeddings.mp4 (272.39 MB)
3 -NLP Applications.mp4 (202.6 MB)
4 -Project - Build a basic text classification model.mp4 (71.94 MB)
1 -Basics of Image Processing.mp4 (266.19 MB)
2 -Object Recognition and Feature Extraction.mp4 (122.25 MB)
3 -Applications in Vision.mp4 (258.56 MB)
4 -Project - Create a pipeline for image classification.mp4 (146.33 MB)
1 -Fundamentals of Search.mp4 (293.46 MB)
2 -Optimization Techniques.mp4 (220.51 MB)
3 -Applications of Search in AI.mp4 (166.39 MB)
4 -Project - Implement A search.mp4 (116.87 MB)
1 -Introduction to Reinforcement Learning.mp4 (148.56 MB)
2 -Q-Learning Basics.mp4 (222.19 MB)
1 -Introduction to Generative AI.mp4 (117.62 MB)
2 -Working with Autoencoders.mp4 (174.66 MB)
3 -Applications of Generative AI.mp4 (65.06 MB)
4 -Project - Generate realistic text using an AI-based language model.mp4 (133.5 MB)
1 -Exploratory Data Analysis.mp4 (88.63 MB)
2 -Data Cleaning Handling missing data.mp4 (185.58 MB)
3 -Data Cleaning Removing duplicates and fixing inconsistencies.mp4 (83.11 MB)
4 -Feature Scaling.mp4 (152.86 MB)
5 -Data Transformation and Encoding.mp4 (115.04 MB)
6 -Splitting Data TrainTest Split.mp4 (147.22 MB)
7 -Practical Implementation.mp4 (121.62 MB)
1 -Introduction to Linear Regression.mp4 (95.01 MB)
2 -Implementing Linear Regression in Python.mp4 (69.31 MB)
3 -Polynomial Regression.mp4 (109.89 MB)
4 -Ridge, Lasso, and Elastic Net Regression.mp4 (166.54 MB)
5 -Project - Predicting Housing Prices.mp4 (190.84 MB)
1 -Understanding Logistic Regression.mp4 (216.07 MB)
2 -Implementing Logistic Regression in Python.mp4 (202.72 MB)
3 -Decision Trees.mp4 (159.51 MB)
4 -k-Nearest Neighbors (k-NN).mp4 (119.44 MB)
5 -Support Vector Machines (SVM).mp4 (117.97 MB)
6 -Project - Comparing Classification Models.mp4 (97.06 MB)
1 -Introduction to Ensemble Learning.mp4 (115.66 MB)
2 -Random Forest.mp4 (171.75 MB)
3 -Gradient Boosting Algorithms.mp4 (155.52 MB)
4 -Project - Credit card fraud detection using ensemble methods.mp4 (217.16 MB)
1 -K-Means Clustering.mp4 (196.82 MB)
2 -Hierarchical Clustering.mp4 (131 MB)
3 -Density-Based Clustering.mp4 (130.66 MB)
4 -Project - Customer Segmentation Using Clustering Algorithms.mp4 (131.85 MB)
1 -Principal Component Analysis (PCA).mp4 (138.6 MB)
2 -t-SNE (t-Distributed Stochastic Neighbor Embedding).mp4 (179.02 MB)
3 -Autoencoders.mp4 (243.29 MB)
4 -Project - Visualizing Wine Data Using PCA and t-SNE.mp4 (98.89 MB)
1 -Introduction to Association Rules - Market Basket Analysis.mp4 (139.64 MB)
2 -Apriori Algorithm.mp4 (97.58 MB)
3 -FP-Growth Algorithm.mp4 (123.5 MB)
4 -Project - Market Basket Analysis for E-commerce Data.mp4 (63.12 MB)
1 -Course Overview.mp4 (26.21 MB)
2 -What is Artificial Intelligence.mp4 (119.91 MB)
3 -AI vs ML vs DL.mp4 (42.76 MB)
4 -Core Components of AI.mp4 (42.13 MB)
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