Python for Data Science and Machine Learning Bootcamp
تطوير البرمجيات / علم البيانات

Python for Data Science and Machine Learning Bootcamp

Learn how to use NumPy, Pandas, Seaborn, Plotly, Machine Learning, Tensorflow, and more!

الإلتحاق

0 طلاب

المستوى

مبتدئ 

اللغة

الإنجليزية
Python for Data Science and Machine Learning Bootcamp
هذه الدورة التدريبية تتضمّن:
  • 25ساعة 08دقيقة
  • 166 محاضرة
  • 294 أصول قابلة للتحميل
  • متاحة مدى الحياة
  • مشاهدة عبر الموبايل والتلفزيون
  • شهادة عند الإنتهاء

ملخص

ما الذي سيتعلّمه المتعلّمون في هذه الدورة التدريبية؟
  • Use Python for Data Science and Machine Learning
  • Use Spark for Big Data Analysis
  • Implement Machine Learning Algorithms
  • Learn to use NumPy for Numerical Data
  • Learn to use Pandas for Data Analysis
  • Learn to use Matplotlib for Python Plotting
  • Learn to use Seaborn for statistical plots
  • Use Plotly for interactive dynamic visualizations
  • Use SciKit-Learn for Machine Learning Tasks
  • K-Means Clustering
  • Logistic Regression
  • Linear Regression
  • Random Forest and Decision Trees
  • Natural Language Processing and Spam Filters
  • Neural Networks
  • Support Vector Machines
ما هي الشروط أو المتطلبات الأساسية لأخذ دورتك التدريبية؟
  • Some programming experience
  • Admin permissions to download files
لمن هذه الدورة التدريبية؟
  • This course is meant for people with at least some programming experience
الوصف
علامات الدورة التدريبية

محتوى الدورة التدريبية

  • 27 قسم
  • 166 محاضرة
  • 25ساعة 08دقيقة إجمالي طول المدة
Course Introduction
07دقيقة
3 محاضرات

Course Introduction

Updates to Notebook Zip
0:01:00
Jupyter Notebooks
0:13:48
Optional: Virtual Environments
0:09:51
Welcome to the Python Crash Course Section!
0:01:00
Introduction to Python Crash Course
0:01:26
Python Crash Course - Part 1
0:19:29
Python Crash Course - Part 2
0:15:14
Python Crash Course - Part 3
0:16:39
Python Crash Course - Part 4
0:15:37
Python Crash Course Exercises - Overview
0:03:35
Python Crash Course Exercises - Solutions
0:11:56
Welcome to the NumPy Section!
0:01:00
Introduction to Numpy
0:02:12
Numpy Arrays
0:16:49
Quick Note on Array Indexing
0:01:00
Numpy Array Indexing
0:18:23
Numpy Operations
0:07:04
Numpy Exercises Overview
0:02:46
Numpy Exercises Solutions
0:15:31
Welcome to the Pandas Section!
0:01:00
Introduction to Pandas
0:01:44
Series
0:10:39
DataFrames - Part 1
0:15:31
DataFrames - Part 2
0:17:10
DataFrames - Part 3
0:09:12
Missing Data
0:06:19
Groupby
0:06:48
Merging Joining and Concatenating
0:08:55
Operations
0:12:04
Data Input and Output
0:14:00
Note on SF Salary Exercise
0:01:00
SF Salaries Exercise Overview
0:01:55
SF Salaries Solutions
0:15:25
Ecommerce Purchases Exercise Overview
0:02:11
Ecommerce Purchases Exercise Solutions
0:15:12
Matplotlib Part 1
0:16:57
Matplotlib Part 2
0:15:51
Matplotlib Part 3
0:11:51
Matplotlib Exercises Overview
0:01:46
Matplotlib Exercises - Solutions
0:10:19
Introduction to Seaborn
0:02:58
Categorical Plots
0:17:17
Matrix Plots
0:10:14
Grids
0:08:30
Regression Plots
0:07:13
Style and Color
0:08:21
Seaborn Exercise Overview
0:01:53
Seaborn Exercise Solutions
0:07:08
Pandas Built-in Data Visualization
0:13:27
Pandas Data Visualization Exercise
0:01:22
Pandas Data Visualization Exercise- Solutions
0:08:55
READ ME FIRST BEFORE PLOTLY PLEASE!
0:01:00
Plotly and Cufflinks
0:18:38
Choropleth Maps - Part 1 - USA
0:19:26
Choropleth Maps - Part 2 - World
0:06:53
Choropleth Exercises
0:03:11
Choropleth Exercises - Solutions
0:10:01
911 Calls Solutions - Part 1
0:14:29
911 Calls Solutions - Part 2
0:17:37
Bank Data
0:01:00
Finance Data Project Overview
0:03:06
Finance Project - Solutions Part 1
0:16:13
Finance Project - Solutions Part 2
0:18:11
Finance Project - Solutions Part 3
0:06:23
Welcome to Machine Learning. Here are a few resources to get you started!
0:01:00
Welcome to the Machine Learning Section!
0:01:00
Supervised Learning Overview
0:08:21
Evaluating Performance - Classification Error Metrics
0:16:37
Evaluating Performance - Regression Error Metrics
0:05:36
Machine Learning with Python
0:09:27
Linear Regression Theory
0:04:33
model_selection Updates for SciKit Learn 0.18
0:01:00
Linear Regression with Python - Part 1
0:18:16
Linear Regression with Python - Part 2
0:07:05
Linear Regression Project Overview
0:02:31
Linear Regression Project Solution
0:18:43
Bias Variance Trade-Off
0:06:25
Logistic Regression Theory
0:11:53
Logistic Regression with Python - Part 1
0:17:43
Logistic Regression with Python - Part 2
0:16:57
Logistic Regression with Python - Part 3
0:08:15
Logistic Regression Project Overview
0:01:36
Logistic Regression Project Solutions
0:11:05
KNN Theory
0:05:38
KNN with Python
0:19:39
KNN Project Overview
0:01:11
KNN Project Solutions
0:14:14
Introduction to Tree Methods
0:06:52
Decision Trees and Random Forest with Python
0:13:57
Decision Trees and Random Forest Project Overview
0:03:10
Decision Trees and Random Forest Solutions Part 1
0:12:13
Decision Trees and Random Forest Solutions Part 2
0:08:46
SVM Theory
0:04:36
Support Vector Machines with Python
0:17:52
SVM Project Overview
0:02:21
SVM Project Solutions
0:10:09
K Means Algorithm Theory
0:05:15
K Means with Python
0:12:35
K Means Project Overview
0:02:53
K Means Project Solutions
0:16:38
Principal Component Analysis
0:03:26
PCA with Python
0:16:58
Recommender Systems
0:04:13
Recommender Systems with Python - Part 1
0:13:36
Recommender Systems with Python - Part 2
0:13:21
Natural Language Processing Theory
0:05:06
NLP with Python - Part 1
0:16:02
NLP with Python - Part 2
0:18:46
NLP with Python - Part 3
0:17:30
NLP Project Overview
0:02:04
NLP Project Solutions
0:19:26
Download TensorFlow Notebooks Here
0:01:00
Quick Check for Notes
0:01:00
Welcome to the Deep Learning Section!
0:01:00
Introduction to Artificial Neural Networks (ANN)
0:02:15
Installing Tensorflow
0:01:00
Perceptron Model
0:10:39
Neural Networks
0:07:19
Activation Functions
0:10:39
Multi-Class Classification Considerations
0:10:34
Cost Functions and Gradient Descent
0:18:13
Backpropagation
0:14:47
TensorFlow vs Keras
0:02:13
TF Syntax Basics - Part One - Preparing the Data
0:10:48
TF Syntax Basics - Part Two - Creating and Training the Model
0:13:59
TF Syntax Basics - Part Three - Model Evaluation
0:12:56
TF Regression Code Along - Exploratory Data Analysis
0:18:50
TF Regression Code Along - Exploratory Data Analysis - Continued
0:13:15
TF Regression Code Along - Data Preprocessing and Creating a Model
0:08:42
TF Regression Code Along - Model Evaluation and Predictions
0:11:23
TF Classification Code Along - EDA and Preprocessing
0:08:05
TF Classification - Dealing with Overfitting and Evaluation
0:16:50
TensorFlow 2.0 Project Options Overview
0:01:40
TensorFlow 2.0 Project Notebook Overview
0:07:41
Keras Project Solutions - Dealing with Missing Data
0:20:35
Keras Project Solutions - Dealing with Missing Data - Part Two
0:14:46
Keras Project Solutions - Categorical Data
0:12:02
Keras Project Solutions - Data PreProcessing
0:17:23
Keras Project Solutions - Data PreProcessing
0:03:45
Keras Project Solutions - Creating and Training a Model
0:03:57
Keras Project Solutions - Model Evaluation
0:09:42
Tensorboard
0:18:22
Welcome to the Big Data Section!
0:01:00
Big Data Overview
0:05:31
Spark Overview
0:08:59
Local Spark Set-Up
0:01:00
AWS Account Set-Up
0:04:13
Quick Note on AWS Security
0:01:00
EC2 Instance Set-Up
0:16:18
SSH with Mac or Linux
0:04:49
PySpark Setup
0:23:48
Lambda Expressions Review
0:05:26
Introduction to Spark and Python
0:08:16
RDD Transformations and Actions
0:23:08
Bonus Lecture
0:01:00

نبذة عن المعلّم

زويلا ليمكي

زويلا ليمكي
بلد الأصل: جامايكا
بلد الأصل: جامايكا
جامايكا
مكان الإقامة: جامايكا

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1 دورة تدريبية
السيرة الشخصية

مرحبًا بالطلاب! اسمي Zoila Lemke ولدي خبرة في إرشاد كل من البالغين والأطفال. بصفتي مدرسًا أول ، تعاونت في المشروع في عام 1997 مع مديرية التربية والتعليم وكلية ترينيتي بإسبانيا. لقد قمت بتدريس اللغات الصينية واليابانية والعبرية الإسرائيلية في تجربتي التعليمية. قبل ذلك ، عملت في العديد من المؤسسات مثل مدرسة اللغة الإنجليزية التابعة لجمعية رعاية زوجات الجيش ومركز هندوستان تايمز التعليمي ، حيث قمت بتدريس المتعلمين من مختلف القدرات. أنا شخص سعيد يستمتع بالتفاعل مع الآخرين.

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