Python: Python For Data Science And Machine Learning

https://www.fandangotrading.com/9axu18v4hwx Introduction Part One – An Introduction to Data Science and Machine Learning What Is Data Science? How Important Is Data Science? Data Science Limitations What Is Machine Learning? How Important Is Machine Learning? Machine Learning Limitations Data Science vs. Machine Learning Part Two – Introducing NumPy What Is NumPy Library? How to Create a NumPy Array Shaping and Reshaping a NumPy array Index and Slice a NumPy Array Stack and Concatenate NumPy Arrays Broadcasting in NumPy Arrays NumPy Ufuncs Doing Math with NumPy Arrays NumPy Arrays and Images Part Three – Data Manipulation with Pandas Question One: How Do I Create a Pandas DataFrame? Question Two – How Do I Select a Column or Index from a DataFrame? Question Three: How Do I Add a Row, Column, or Index to a DataFrame? Question Four: How Do I Delete Indices, Rows, or Columns From a Data Frame? Question Five: How Do I Rename the Columns or Index of a DataFrame? Question Six: How Do I Format the DataFrame Data? Question Seven: How Do I Create an Empty DataFrame? Question Eight: When I Import Data, Will Pandas Recognize Dates? Question Nine: When Should a DataFrame Be Reshaped? Why and How? Question Ten: How Do I Iterate Over a DataFrame? Question Eleven: How Do I Write a DataFrame to a File? Part Four – Data Visualization with Matplotlib and Seaborn Using Matplotlib to Generate Histograms Using Matplotlib to Generate Scatter Plots Using Matplotlib to Generate Bar Charts Using Matplotlib to Generate Pie Charts Visualizing Data with Seaborn Using Seaborn to Generate Histograms Using Seaborn to Generate Scatter Plots Using Seaborn to Generate Heatmaps Using Seaborn to Generate Pairs Plot Part Five – An In-Depth Guide to Machine Learning Machine Learning Past to Present Machine Learning Features Different Types of Machine Learning Common Machine Learning Algorithms Gaussian Naive Bayes classifier K-Nearest Neighbors Support Vector Machine Learning Algorithm Fitting Support Vector Machines Linear Regression Machine Learning Algorithm Logistic Regression Machine Learning Algorithm A Logistic Regression Model Decision Tree Machine Learning Algorithm Random Forest Machine Learning Algorithm Artificial Neural Networks Machine Learning Algorithm Machine Learning Steps Evaluating a Machine Learning Model Model Evaluation Metrics Regression Metrics Implementing Machine Learning Algorithms with Python Advantages and Disadvantages of Machine Learning Conclusion ReferencesIntroduction