Course Content
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Dear, to register for the 6 months AI and Data Science Mentorship Program, click this link and fill the form give there: https://shorturl.at/fuMX6
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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
    Rana Anjum Sharif 11 months ago
    Done
    Reply
    Muhammad Rameez 11 months ago
    Done
    Reply
    Muhammad Rameez 11 months ago
    Done
    Reply
    junaid amin 1 year ago
    well explained
    Reply
    Faheem Ullah 1 year ago
    MashaAllah Explained well
    Reply
    tayyab Ali 1 year ago
    I learned in this lecture with 100% practice.
    Reply
    Sibtain Ali 1 year ago
    I have done this video with 100% practice.
    Reply
    Javed Ali 1 year ago
    And I also learned ML algorithm of K-Nearest Neighbors ( KNN ) in PythonSteps of K-Nearest Neighbors ( KNN ) and Example of KNN Classifier on IRIS data Set1-Import libraries 2-Load the data set of IRIS 3-Split the data in X and y 4-Train test split the data 5-Fit the model on training data 6-Predict the species for the test data 7-Evaluate the model 8-plot the confusion matrix 9-Save the model 10-Load the modelAnd the Steps of K-Nearest Neighbors ( KNN ) and Example of KNN Regression on the TIPS data set1-Load the data set 2-Split the data into X and y 3-Encode the categorical columns using for lopp and le 4-Train test: split the data and run the model 5-Fit the model to the training data 6-Predict the model 7-Evaluate the model 8-Predict the specific valueALLAH PAK aap ko sahat o aafiat wali lambi umar ata kray aor ap ko dono jahan ki bhalian naseeb farmaey,Ameen.
    Reply
    Shahid Umar 1 year ago
    A better understanding of the KNN algorithm through Python coding in this lecture.
    Reply
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