Course Content
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Day-17: Complete EDA on Google PlayStore Apps
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Day-25: Quiz Time, Data Visualization-4
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Day-27: Data Scaling/Normalization/standardization and Encoding
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Day-30: NumPy (Part-3)
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Day-31: NumPy (Part-4)
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Day-32a: NumPy (Part-5)
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Day-32b: Data Preprocessing / Data Wrangling
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Day-37: Algebra in Data Science
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Day-56: Statistics for Data Science (Part-5)
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Day-69: Machine Learning (Part-3)
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Day-75: Machine Learning (Part-9)
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Day-81: Machine Learning (Part-15)-Evaluation Metrics
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Day-82: Machine Learning (Part-16)-Metrics for Classification
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Day-85: Machine Learning (Part-19)
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Day-89: Machine Learning (Part-23)
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Day-91: Machine Learning (Part-25)
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Day-93: Machine Learning (Part-27)
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Day-117: Deep Learning (Part-14)-Complete CNN Project
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Day-119: Deep Learning (Part-16)-Natural Language Processing (NLP)
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Day-121: Time Series Analysis (Part-1)
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Day-123: Time Series Analysis (Part-3)
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Day-128: Time Series Analysis (Part-8): Complete Project
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Day-129: git & GitHub Crash Course
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Day-131: Improving Machine/Deep Learning Model’s Performance
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Day-133: Transfer Learning and Pre-trained Models (Part-2)
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Day-134 Transfer Learning and Pre-trained Models (Part-3)
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Day-137: Generative AI (Part-3)
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Day-139: Generative AI (Part-5)-Tensorboard
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Day-145: Streamlit for webapp development and deployment (Part-1)
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Day-146: Streamlit for webapp development and deployment (Part-2)
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Day-147: Streamlit for webapp development and deployment (Part-3)
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Day-148: Streamlit for webapp development and deployment (Part-4)
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Day-149: Streamlit for webapp development and deployment (Part-5)
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Day-150: Streamlit for webapp development and deployment (Part-6)
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Day-151: Streamlit for webapp development and deployment (Part-7)
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Day-152: Streamlit for webapp development and deployment (Part-8)
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Day-153: Streamlit for webapp development and deployment (Part-9)
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Day-154: Streamlit for webapp development and deployment (Part-10)
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Day-155: Streamlit for webapp development and deployment (Part-11)
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Day-156: Streamlit for webapp development and deployment (Part-12)
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Day-157: Streamlit for webapp development and deployment (Part-13)
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How to Earn using Data Science and AI skills
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Day-160: Flask for web app development (Part-3)
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Day-161: Flask for web app development (Part-4)
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Day-162: Flask for web app development (Part-5)
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Day-163: Flask for web app development (Part-6)
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Day-164: Flask for web app development (Part-7)
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Day-165: Flask for web app deployment (Part-8)
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Day-167: FastAPI (Part-2)
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Day-168: FastAPI (Part-3)
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Day-169: FastAPI (Part-4)
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Day-170: FastAPI (Part-5)
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Day-171: FastAPI (Part-6)
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Day-174: FastAPI (Part-9)
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Six months of AI and Data Science Mentorship Program
    Join the conversation
    Najeeb Ullah 3 days ago
    done once again
    Reply
    Shahid Umar 5 months ago
    There are thirteen types of neural network define in this lecture
    Reply
    tayyab Ali 5 months ago
    I learned in this lecture about type of neural network (feedforward neural network (FNN), convolutional neural network (CNNs), recurrent neural network (RNNs), long-short memory networks (LSTMs), radial basis function (RBF) neural networks, self-organizing maps (SOMs), deep belief networks (DBNs), generative adversarial networks (GANs), autoencoders, modular neural networks, neural turning machines (NTMs), capsule neural network).
    Reply
    Sibtain Ali 5 months ago
    I learned in this video (1. Feedforward Neural Network (FNN):, 2. Recurrent Neural Network (RNN):, 3. Convolutional Neural Network (CNN):, 4. Long Short-Term Memory (LSTM) Networks, 5. Generative Adversarial Network (GAN):, 6. Autoencoder, 7. Radial Basis Function (RBF) Network, and 8. Self-Organizing Map (SOM):).
    Reply
    Shadat Ali 5 months ago
    We learned, in this lecture, types of neural network. 1-feedforward neutral network (FNN) for basic and simple classification and regression task..2-Convolutional neutral network(CNN):it used for image recognition , video analysis
    Reply
    Javed Ali 5 months ago
    I learned in this lecture about types of Neural Network which are1-Feedforward Neural Network (FNN) (Simple, basic classification and regression task)2-Convolutional Neural Network (CNN) (Moderate, image recognition,video analysis,image classification)3-Recurrent Neural Networks (RNNs) (Modrate, sequence modeling, NLP, speech recognition)4-Long Short-Term Memory Networks (LSTMs) (Modrate, text generation, machine translation, and learning long-term dependencies in sequence data)5-Radial Basis Function (RBF) Neural Network (Modrate, function approximation, time series prediction)6-Self-Organizing Maps (SOMs) (Modrate visualization of high-dimensional data,dimensionality reduction, clustering)7-Deep Belief Networks (DBNs) (HIgh, image recognition, video recognition, motion capture data analysis)8-Generative Adversarial Network (GANs) (High, generate new data sample like image, texts,etc)9-Autoencoder (High, dimensionality reduction, feature learning, noise reduction, and data generation)10-Modular Neural Network (High, complex pattern recognition problems)11-Neural Training Machines (NTMs) (Very High, complex problem-solving tasks)12-Capsule Neural Network (Very High, image analysis, and object recognition).ALLAH PAK aap ko sahat o aafiyat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey aur aap ke walid-e-mohtram ko karwat karwat jannat ata farmaye,Ameen.
    Reply
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