The Data Science & Machine Learning Bootcamp in Python

The Data Science & Machine Learning Bootcamp in Python MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Genre: eLearning | Language: English + .srt | Duration: 277 lectures (12h 5m) | Size: 4.94 GB Learn Python,NumPy,Pandas,Matplotlib,Seaborn,Scikit-learn,Dask,LightGBM,XGBoost,CatBoost,Streamlit,Power BI & much more What you'll learn: Python for Data Science The Data Science Process NumPy for Numerical Computation Pandas for Data Manipulation Matplotlib for Visualization Seaborn for Beautiful Visuals Plotly for Interactive Visuals Introduction to Machine Learning Dask for Big Data LightGBM XGBoost CatBoost Linear Regression Logistic Regression Decision Trees Random Forest Deep Learning using Keras and TensorFlow Artificial Neural Networks How Artificial Neural Networks Work How Artificial Neural Networks Learn Loss Functions used in Artificial Neural Networks Activation Functions used in Artificial Neural Networks Cost Functions used in Artificial Neural Networks Optimizer Functions used in Artificial Neural Networks What Backpropagation is Different Types of Gradient Descent How to Choose an Activation Function Preparing your Data for Deep Learning Models Monitoring Loss Functions Monitoring Model Metrics Use of CallBacks in Deep Learning Fighting overfitting in TensorFlow Convolutional Neural Networks Natural Language Processing Support Vector Machines KNearest Neighbors T-Test Chi-square Test K-Means Clustering Principal Component Analysis Flask Association Rule Mining - Apriori Building Dashboards in Power BI Requirements A great sense of curiosity! Description In this course, you'll learn how to get started in data science. You don't need any prior knowledge in programming. We'll teach you the Python basics you need to get started. Here are the items we'll cover in this course The Data Science Process Python for Data Science NumPy for Numerical Computation Pandas for Data Manipulation Matplotlib for Visualization Seaborn for Beautiful Visuals Plotly for Interactive Visuals Introduction to Machine Learning Dask for Big Data Power BI Desktop Association Rule Mining - Apriori Deep Learning & Next Steps For the machine learning section here are some items we'll cover : How Algorithms Work Advantages & Disadvantages of Various Algorithms Feature Importances Metrics Cross-Validation Fighting Overfitting Hyperparameter Tuning Handling Imbalanced Data TensorFlow & Keras Automated Machine Learning(AutoML) Natural Language Processing Who this course is for People who would like to get started with data science and machine learning without any prior knowledge Persons who would like to refresh their data science and machine learning knowledge https://anonymz.com/?https://www.udemy.com/course/data-science-bootcamp-in-python/

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