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25.08 GB | 45min 41s | mp4 | 1280X720 | 16:9
Genre: eLearning | Language : English
Files Included :
1 Introduction to Week 1 Python Programming Basics.mp4 (863.59 KB)
10 Code files.zip (30.43 MB)
2 Day 1 Introduction to Python and Development Setup.mp4 (37.46 MB)
3 Day 2 Control Flow in Python.mp4 (222.58 MB)
4 Day 3 Functions and Modules.mp4 (139.47 MB)
5 Day 4 Data Structures (Lists, Tuples, Dictionaries, Sets).mp4 (200.51 MB)
6 Day 5 Working with Strings.mp4 (152.35 MB)
7 Day 6 File Handling.mp4 (148.61 MB)
8 Day 7 Pythonic Code and Project Work.mp4 (309.32 MB)
1 Introduction to Week 2 Data Science Essentials.mp4 (3.12 MB)
2 Day 1 Introduction to NumPy for Numerical Computing.mp4 (162.07 MB)
3 Day 2 Advanced NumPy Operations.mp4 (148.47 MB)
4 Day 3 Introduction to Pandas for Data Manipulation.mp4 (152.53 MB)
5 Day 4 Data Cleaning and Preparation with Pandas.mp4 (155.84 MB)
6 Day 5 Data Aggregation and Grouping in Pandas.mp4 (98.99 MB)
7 Day 6 Data Visualization with Matplotlib and Seaborn.mp4 (221.74 MB)
8 Day 7 Exploratory Data Analysis (EDA) Project.mp4 (168.44 MB)
1 Introduction to Week 3 Mathematics for Machine Learning.mp4 (3.23 MB)
2 Day 1 Linear Algebra Fundamentals.mp4 (143.86 MB)
3 Day 2 Advanced Linear Algebra Concepts.mp4 (134.63 MB)
4 Day 3 Calculus for Machine Learning (Derivatives).mp4 (123.23 MB)
5 Day 4 Calculus for Machine Learning (Integrals and Optimization).mp4 (103.5 MB)
6 Day 5 Probability Theory and Distributions.mp4 (179.14 MB)
7 Day 6 Statistics Fundamentals.mp4 (137.21 MB)
8 Day 7 Math-Driven Mini Project - Linear Regression from Scratch.mp4 (113.28 MB)
1 Introduction to Week 4 Probability and Statistics for Machine Learning.mp4 (3.56 MB)
2 Day 1 Probability Theory and Random Variables.mp4 (122.64 MB)
3 Day 2 Probability Distributions in Machine Learning.mp4 (116.05 MB)
4 Day 3 Statistical Inference - Estimation and Confidence Intervals.mp4 (112.63 MB)
5 Day 4 Hypothesis Testing and P-Values.mp4 (70.76 MB)
6 Day 5 Types of Hypothesis Tests.mp4 (132.71 MB)
7 Day 6 Correlation and Regression Analysis.mp4 (124.75 MB)
8 Day 7 Statistical Analysis Project - Analyzing Real-World Data.mp4 (208.52 MB)
1 Introduction to Week 5 Introduction to Machine Learning.mp4 (3.61 MB)
2 Day 1 Machine Learning Basics and Terminology.mp4 (98.32 MB)
3 Day 2 Introduction to Supervised Learning and Regression Models.mp4 (100.56 MB)
4 Day 3 Advanced Regression Models - Polynomial Regression and Regularization.mp4 (304.55 MB)
5 Day 4 Introduction to Classification and Logistic Regression.mp4 (186.99 MB)
6 Day 5 Model Evaluation and Cross-Validation.mp4 (112.93 MB)
7 Day 6 k-Nearest Neighbors (k-NN) Algorithm.mp4 (139.55 MB)
8 Day 7 Supervised Learning Mini Project.mp4 (227.71 MB)
1 Introduction to Week 6 Feature Engineering and Model Evaluation.mp4 (2.94 MB)
2 Day 1 Introduction to Feature Engineering.mp4 (105.89 MB)
3 Day 2 Data Scaling and Normalization.mp4 (131.67 MB)
4 Day 3 Encoding Categorical Variables.mp4 (132.09 MB)
5 Day 4 Feature Selection Techniques.mp4 (128.25 MB)
6 Day 5 Creating and Transforming Features.mp4 (140.81 MB)
7 Day 6 Model Evaluation Techniques.mp4 (117.36 MB)
8 Day 7 Cross-Validation and Hyperparameter Tuning.mp4 (162.38 MB)
1 Introduction to Week 7 Advanced Machine Learning Algorithms.mp4 (2.81 MB)
2 Day 1 Introduction to Ensemble Learning.mp4 (115.04 MB)
3 Day 2 Bagging and Random Forests.mp4 (106.96 MB)
4 Day 3 Boosting and Gradient Boosting.mp4 (127.19 MB)
5 Day 4 Introduction to XGBoost.mp4 (153.78 MB)
6 Day 5 LightGBM and CatBoost.mp4 (167.05 MB)
7 Day 6 Handling Imbalanced Data.mp4 (139.88 MB)
8 Day 7 Ensemble Learning Project - Comparing Models on a Real Dataset.mp4 (207.31 MB)
1 Introduction to Week 8 Model Tuning and Optimization.mp4 (4.24 MB)
2 Day 1 Introduction to Hyperparameter Tuning.mp4 (109.31 MB)
3 Day 2 Grid Search and Random Search.mp4 (136.05 MB)
4 Day 3 Advanced Hyperparameter Tuning with Bayesian Optimization.mp4 (245.05 MB)
5 Day 4 Regularization Techniques for Model Optimization.mp4 (116.63 MB)
6 Day 5 Cross-Validation and Model Evaluation Techniques.mp4 (102.35 MB)
7 Day 6 Automated Hyperparameter Tuning with GridSearchCV and RandomizedSearchCV.mp4 (171.42 MB)
8 Day 7 Optimization Project - Building and Tuning a Final Model.mp4 (207.87 MB)
1 Introduction to Week 9 Neural Networks and Deep Learning Fundamentals.mp4 (3.75 MB)
2 Day 1 Introduction to Deep Learning and Neural Networks.mp4 (110.76 MB)
3 Day 2 Forward Propagation and Activation Functions.mp4 (109.86 MB)
4 Day 3 Loss Functions and Backpropagation.mp4 (118.05 MB)
5 Day 4 Gradient Descent and Optimization Techniques.mp4 (180.92 MB)
6 Day 5 Building Neural Networks with TensorFlow and Keras.mp4 (153.83 MB)
7 Day 6 Building Neural Networks with PyTorch.mp4 (240.33 MB)
8 Day 7 Neural Network Project - Image Classification on CIFAR-10.mp4 (200.65 MB)
1 Introduction to Week 10 Convolutional Neural Networks (CNNs).mp4 (4.17 MB)
2 Day 1 Introduction to Convolutional Neural Networks.mp4 (212.69 MB)
3 Day 2 Convolutional Layers and Filters.mp4 (189.62 MB)
4 Day 3 Pooling Layers and Dimensionality Reduction.mp4 (210.6 MB)
5 Day 4 Building CNN Architectures with Keras and TensorFlow.mp4 (142.42 MB)
6 Day 5 Building CNN Architectures with PyTorch.mp4 (204.84 MB)
7 Day 6 Regularization and Data Augmentation for CNNs.mp4 (148.73 MB)
8 Day 7 CNN Project - Image Classification on Fashion MNIST or CIFAR-10.mp4 (248.04 MB)
1 Introduction to Week 11 Recurrent Neural Networks (RNNs) and Sequence Modeling.mp4 (4.24 MB)
2 Day 1 Introduction to Sequence Modeling and RNNs.mp4 (275.13 MB)
3 Day 2 Understanding RNN Architecture and Backpropagation Through Time (BPTT).mp4 (212.85 MB)
4 Day 3 Long Short-Term Memory (LSTM) Networks.mp4 (112.55 MB)
5 Day 4 Gated Recurrent Units (GRUs).mp4 (52.73 MB)
6 Day 5 Text Preprocessing and Word Embeddings for RNNs.mp4 (207.54 MB)
7 Day 6 Sequence-to-Sequence Models and Applications.mp4 (401.49 MB)
8 Day 7 RNN Project - Text Generation or Sentiment Analysis.mp4 (156.01 MB)
1 Introduction to Week 12 Transformers and Attention Mechanisms.mp4 (3.98 MB)
2 Day 1 Introduction to Attention Mechanisms.mp4 (110.76 MB)
3 Day 2 Introduction to Transformers Architecture.mp4 (139.41 MB)
4 Day 3 Self-Attention and Multi-Head Attention in Transformers.mp4 (189.43 MB)
5 Day 4 Positional Encoding and Feed-Forward Networks.mp4 (165.81 MB)
6 Day 5 Hands-On with Pre-Trained Transformers - BERT and GPT.mp4 (168.73 MB)
7 Day 6 Advanced Transformers - BERT Variants and GPT-3.mp4 (171.28 MB)
8 Day 7 Transformer Project - Text Summarization or Translation.mp4 (155.37 MB)
1 Introduction to Week 13 Transfer Learning and Fine-Tuning.mp4 (3.21 MB)
2 Day 1 Introduction to Transfer Learning.mp4 (118.9 MB)
3 Day 2 Transfer Learning in Computer Vision.mp4 (234.43 MB)
4 Day 3 Fine-Tuning Techniques in Computer Vision.mp4 (191.41 MB)
5 Day 4 Transfer Learning in NLP.mp4 (142.28 MB)
6 Day 5 Fine-Tuning Techniques in NLP.mp4 (224.19 MB)
7 Day 6 Domain Adaptation and Transfer Learning Challenges.mp4 (128.4 MB)
8 Day 7 Transfer Learning Project - Fine-Tuning for a Custom Task.mp4 (154.23 MB)
1 Whats Next.mp4 (2.87 MB)
10 Random Forests Implementation in Python.mp4 (40.63 MB)
11 Gradient Boosting Implementation in Python.mp4 (41.69 MB)
12 Naive Bayes Implementation in Python.mp4 (36.68 MB)
13 K-Means Clustering Implementation in Python.mp4 (22.78 MB)
14 Hierarchical Clustering Implementation in Python.mp4 (30.22 MB)
15 DBSCAN (Density-Based Spatial Clustering of Applications w Noise) Implementation.mp4 (25.99 MB)
16 Gaussian Mixture Models(GMM) Implementation in Python.mp4 (28.05 MB)
17 Principal Component Analysis (PCA) Implementation in Python.mp4 (28.23 MB)
18 t-Distributed Stochastic Neighbor Embedding (t-SNE) Implementation in Python.mp4 (32.43 MB)
19 Autoencoders Implementation in Python.mp4 (57.76 MB)
2 Introduction to Machine Learning Algorithms.mp4 (13.8 MB)
20 Self-Training Implementation in Python.mp4 (51.96 MB)
21 Q-Learning Implementation in Python.mp4 (64.39 MB)
22 Deep Q-Networks (DQN) Implementation in Python.mp4 (113.06 MB)
23 Policy Gradient Methods Implementation in Python.mp4 (92.99 MB)
24 One-Class SVM Implementation in Python.mp4 (28.88 MB)
25 Isolation Forest Implementation in Python.mp4 (32.42 MB)
26 Convolutional Neural Networks (CNNs) Implementation in Python.mp4 (64.69 MB)
27 Recurrent Neural Networks (RNNs) Implementation in Python.mp4 (58.25 MB)
28 Long Short-Term Memory (LSTM) Implementation in Python.mp4 (55.12 MB)
29 Transformers Implementation in Python.mp4 (92.36 MB)
3 Linear Regression Implementation in Python.mp4 (38.27 MB)
4 Ridge and Lasso Regression Implementation in Python.mp4 (51.7 MB)
5 Polynomial Regression Implementation in Python.mp4 (46.99 MB)
6 Logistic Regression Implementation in Python.mp4 (36.35 MB)
7 K-Nearest Neighbors (KNN) Implementation in Python.mp4 (40.32 MB)
8 Support Vector Machines (SVM) Implementation in Python.mp4 (42.25 MB)
9 Decision Trees Implementation in Python.mp4 (41.03 MB)
1 What is Machine Learning.mp4 (39.24 MB)
2 Introduction to TensorFlow.mp4 (27.4 MB)
3 TensorFlow vs Other Machine Learning frameworks.mp4 (54.63 MB)
4 Installing TensorFlow.mp4 (44.07 MB)
5 Setting up your Development Environment.mp4 (34.8 MB)
6 Verifying the Installation.mp4 (43.42 MB)
1 Introduction to Tensors.mp4 (7.42 MB)
2 Tensor Operations.mp4 (12.61 MB)
3 Constants, Variables, and Placeholders.mp4 (11.11 MB)
4 TensorFlow Computational Graph.mp4 (14.97 MB)
5 Creating and Running a TensorFlow Session.mp4 (8.66 MB)
6 Managing Graphs and Sessions.mp4 (14.85 MB)
7 Building a Simple Feedforward Neural Network.mp4 (21.75 MB)
8 Activation Functions.mp4 (14.07 MB)
9 Loss Functions and Optimizers.mp4 (19.67 MB)
1 Introduction to Keras API.mp4 (18.62 MB)
2 Building Complex Models with Keras.mp4 (15.83 MB)
3 Training and Evaluating Models.mp4 (18.04 MB)
4 Introduction to CNNs.mp4 (15.56 MB)
5 Building and Training CNNs with TensorFlow.mp4 (15.13 MB)
6 Transfer Learning with Pre-trained CNNs.mp4 (16.68 MB)
7 Introduction to RNNs.mp4 (16.76 MB)
8 Building and Training RNNs with TensorFlow.mp4 (11.7 MB)
9 Applications of RNNs Language Modeling, Time Series Prediction.mp4 (11.49 MB)
1 Saving and Loading Models.mp4 (14.81 MB)
2 TensorFlow Serving for Model Deployment.mp4 (16.66 MB)
3 TensorFlow Lite for Mobile and Embedded Devices.mp4 (18.91 MB)
4 Introduction to Distributed Computing with TensorFlow.mp4 (21.1 MB)
5 TensorFlow's Distributed Execution Framework.mp4 (23.39 MB)
6 Scaling TensorFlow with TensorFlow Serving and Kubernetes.mp4 (21.49 MB)
7 Introduction to TFX.mp4 (18.36 MB)
8 Building End-to-End ML Pipelines with TFX.mp4 (15.15 MB)
9 Model Validation, Transform, and Serving with TFX.mp4 (22.09 MB)
1 Image Classification.mp4 (22.12 MB)
2 Natural Language Processing.mp4 (22 MB)
3 Recommender Systems.mp4 (25.57 MB)
4 Object Detection.mp4 (20.17 MB)
5 Building a Sentiment Analysis Model.mp4 (30.84 MB)
6 Creating an Image Recognition System.mp4 (23.78 MB)
7 Developing a Time Series Prediction Model.mp4 (17.18 MB)
8 Implementing a Chatbot.mp4 (29.13 MB)
1 Generative Adversarial Networks (GANs).mp4 (15.31 MB)
2 Reinforcement Learning with TensorFlow.mp4 (15.85 MB)
3 Quantum Machine Learning with TensorFlow Quantum.mp4 (19.17 MB)
4 TensorFlow Documentation and Tutorials.mp4 (13.87 MB)
5 Online Courses and Books.mp4 (10.5 MB)
6 TensorFlow Community and Forums.mp4 (16.38 MB)
7 Summary of Key Concepts.mp4 (14.9 MB)
8 Next Steps in Your TensorFlow Journey.mp4 (12.75 MB)
1 1 Introduction to PyTorch.mp4 (57.06 MB)
10 10 Handling Complex Data.mp4 (51.93 MB)
11 11 Model Deployment and Production.mp4 (53.44 MB)
12 12 Debugging and Troubleshooting.mp4 (61.15 MB)
13 13 Distributed Training and Performance Optimization.mp4 (58.16 MB)
14 14 Custom Layers and Loss Functions.mp4 (54.87 MB)
15 15 Research-oriented Techniques.mp4 (59.92 MB)
16 16 Integration with Other Libraries.mp4 (53.14 MB)
17 17 Contributing to PyTorch and Community Engagement.mp4 (53.78 MB)
2 2 Getting Started with PyTorch.mp4 (48.61 MB)
3 3 Working with Tensors.mp4 (60.01 MB)
4 4 Autograd and Dynamic Computation Graphs.mp4 (45.16 MB)
5 5 Building Simple Neural Networks.mp4 (59.99 MB)
6 6 Loading and Preprocessing Data.mp4 (56.9 MB)
7 7 Model Evaluation and Validation.mp4 (65.09 MB)
8 8 Advanced Neural Network Architectures.mp4 (76.77 MB)
9 9 Transfer Learning and Fine-Tuning.mp4 (52.29 MB)
1 1 Introduction to LangChain and Language Models.mp4 (68.86 MB)
2 2 Project 1 Simple Text-Based Question Answering Bot.mp4 (128.22 MB)
3 3 Project 2 Sentiment Analysis with LangChain.mp4 (74.64 MB)
4 4 Project 3 Document Summarization Tool.mp4 (71.84 MB)
5 5 Project 4 Keyword Extraction from Text.mp4 (49.44 MB)
6 6 Project 5 LangChain-Powered Chatbot.mp4 (55.66 MB)
1 Part 1 1 Understanding AI Agents - How AI Agents Function.mp4 (16.15 MB)
10 Part 3 4 LangGraph for Stateful AI Agents.mp4 (25.36 MB)
11 Part 3 5 CrewAI for Collaborative AI Agents.mp4 (32.08 MB)
12 Part 4 1 Applications of AI Agents - AI Agents in Business Operations.mp4 (22.97 MB)
13 Part 4 2 AI Agents in Healthcare.mp4 (23.77 MB)
14 Part 4 3 AI Agents in Financial Systems.mp4 (28.97 MB)
15 Part 4 4 AI Agents in Entertainment.mp4 (22.21 MB)
16 Part 4 5 AI Agents in Smart Homes and IoT.mp4 (27.53 MB)
17 Part 5 1 Future Trends and Ethical Implications - The Future of AI Agents.mp4 (28.87 MB)
18 Part 5 2 Ethics in AI Agent Development.mp4 (21.33 MB)
19 Part 5 3 Legal and Regulatory Challenges for AI Agents.mp4 (28.01 MB)
2 Part 1 2 - Introduction to AI Agents.mp4 (22.13 MB)
20 Part 6 1 Broader Impact of AI Agents - Social and Economic Impacts of AI Agents.mp4 (24.71 MB)
21 Part 6 2 AI Agents and Human Collaboration.mp4 (25.73 MB)
22 Part 6 3 The Role of AI Agents in Scientific Research.mp4 (23.64 MB)
23 Part 6 4 AI Agents in Public Safety and National Defense.mp4 (26.25 MB)
3 Part 1 3 Types of AI Agents.mp4 (21.04 MB)
4 Part 2 1 Technologies Behind AI Agents - Machine Learning and AI Agents.mp4 (28.82 MB)
5 Part 2 2 Natural Language Processing in AI Agents.mp4 (28.11 MB)
6 Part 2 3 AI Agents in Robotics.mp4 (29.13 MB)
7 Part 3 1 AI Agent Frameworks & Architectures - AI Agent Development Frameworks.mp4 (39.03 MB)
8 Part 3 2 Overview of AutoGPT for AI Agents.mp4 (19.87 MB)
9 Part 3 3 IBM Bee Framework for AI Agents.mp4 (27.33 MB)
1 1 Hands-on AutoGen IBM Bee LangGraph CrewAI AutoGPT.mp4 (31.98 MB)
2 2 Hands-on AutoGen.mp4 (88.52 MB)
3 3 Hands-on IBM Bee Framework.mp4 (127.4 MB)
4 4 Hands-on LangGraph.mp4 (118.08 MB)
5 5 Hands-on CrewAI.mp4 (97.73 MB)
6 6 Hands-on AutoGPT.mp4 (45.61 MB)
1 Creating and Publishing GPTs to ChatGPT Store Part 1.mp4 (74.15 MB)
2 Creating and Publishing GPTs to ChatGPT Store Part 2.mp4 (55.47 MB)
3 Creating and Publishing GPTs to ChatGPT Store Part 3.mp4 (85.16 MB)
1 Project 1 AI-Powered Text Summarizer with DeepSeek AI.mp4 (116.31 MB)
1 Project1.zip (3.8 KB)
10 Project 10 E-commerce Product Recommendation Bot with DeepSeek AI.mp4 (83.63 MB)
10 Project10.zip (4 KB)
11 Project 11 Automated Email Responder with DeepSeek AI.mp4 (95.5 MB)
11 Project11.zip (3.51 KB)
12 Project 12 AI-Powered Resume Generator with DeepSeek AI.mp4 (101.62 MB)
12 Project12.zip (3.46 KB)
13 Project 13 AI-Based Meeting Minutes Generator with DeepSeek AI.mp4 (84.06 MB)
13 Project13.zip (3.58 KB)
14 Project 14 Automated PDF Text Extractor with DeepSeek AI.mp4 (108.19 MB)
14 Project14.zip (75.74 KB)
15 Project 15 Content Writer AI with DeepSeek AI.mp4 (96.95 MB)
15 Project15.zip (3.72 KB)
16 Project 16 Code Auto-Completer & Assistant with DeepSeek AI.mp4 (82.46 MB)
16 Project16.zip (3.29 KB)
17 Project 17 SQL Query Generator with DeepSeek AI.mp4 (97.18 MB)
17 Project17.zip (3.76 KB)
18 Project 18 Code Debugger AI with DeepSeek AI.mp4 (82.6 MB)
18 Project18.zip (3.32 KB)
19 Project 19 AI-Based Documentation Generator with DeepSeek AI.mp4 (81.55 MB)
19 Project19.zip (3.28 KB)
2 Project 2 AI-Based Text Generation with DeepSeek AI.mp4 (97.01 MB)
2 Project2.zip (3.17 KB)
20 Project 20 AI-Powered API Tester with DeepSeek AI.mp4 (76.13 MB)
20 Project20.zip (2.04 KB)
21 Project 21 AI-Based Customer Feedback Analyzer with DeepSeek AI.mp4 (91.2 MB)
21 Project21.zip (3.38 KB)
22 Project 22 Real-Time AI News Summarizer with DeepSeek AI.mp4 (99.13 MB)
22 Project22.zip (1.79 KB)
23 Pr
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