The Ultimate Python Machine Learning With Tensorflow Course

Learn everything you need to become a data scientist. Jump into Pandas, PyPlot, MNIST, Keras and more popular libraries.

What you'll learn
Code in Python from scratch
Machine learning theory applied in practical examples
Pandas data manipulation and analysis
PyPlot, a MATLAB-like plotting framework
Build machine learning models in TensorFlow
Build a convolutional neural network
Use Keras with machine learning models
Requirements
No experience necessary
Description
Machine learning is quickly becoming a required skill for every software developer. Enroll now to learn everything you need to know to get up to speed, whether you're a developer or aspiring data scientist. This is the course for you.Your complete Python course for image recognition, data analysis, data visualization and more.Reviews On Our Python Courses:"I know enough Python to be dangerous. Most of the ML classes are so abstract and theoretical that no learning happens. This is the first class where we use concrete examples that I can relate to and allow me to learn. Absolutely love this course!" - Mary T."Yes, this is an amazing start. For someone new in python this is a very simple boot course. I am able to relate to my earlier programming experience with ease!" - Gajendran C."Clear and concise information" - Paul B."Easy to understand and very clear explanations. So far so good!!!" - Alejandro M.When does the course start and finish? The course starts now and never ends! It is a completely self-paced online course - you decide when you start and when you finish. How long do I have access to the course? How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like - across any and all devices you own. What if I am unhappy with the course? We would never want you to be unhappy! If you are unsatisfied with your purchase, contact us in the first 30 days and we will give you a full refund.Mammoth Interactive is a leading online course provider in everything from learning to code to becoming a YouTube star. Mammoth Interactive courses have been featured on Harvard’s edX, Business Insider and more. Over 11 years, Mammoth Interactive has built a global student community with 1.1 million courses sold. Mammoth Interactive has released over 250 courses and 2,500 hours of video content. Founder and CEO John Bura has been programming since 1997 and teaching since 2002. John has created top-selling applications for iOS, Xbox and more. John also runs SaaS company Devonian Apps, building efficiency-minded software for technology workers like you.Don't miss the biggest Python course of the year. This is a once in a lifetime chance to enroll in a massive course.Absolutely no experience necessary. Start with a complete introduction to Python that is perfect for absolute beginners and can also be used a review.Jump into using the most popular libraries and frameworks for working with Python. You'll learn everything you need to become a data scientist. This includes:1. Data Analysis with PandasLearn pandas, a software library written for the Python programming language for data manipulation and analysis.2. Data Visualization with PyPlotLearn pyplot, a MATLAB-like plotting framework enabling you to create a figure, create a plotting area in a figure, plot lines in a plotting area, decorate the plot with labels and much more. Learn it all in this massive course.3. Machine Learning TheoryMachine learning is in high demand and is quickly becoming a requirement on every software engineer's resume. Learn how to solve problems with machine learning before diving into practical examples.4. Introduction to TensorFlowLearn TensorFlow, the most popular plaform enabling ML developers to build and deploy machine learning applications such as neural networks. Build your first linear regression model with TensorFlow. Learn how to build a dataset, model, train and test!5. Image Recognition with MNISTBuild a convolutional neural network (CNN.) Learn how to use Keras with machine learning models.Keras is a neural-network library written in Python capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML. You'll be able to enable fast experimentation with deep neural networks with Keras.All source code is included for each project.If you buy one course this year, this is it. Sign up while spots are open.

Overview

Section 1: Introduction - Learning the Python Basic

Lecture 1 Introduction

Lecture 2 Intro to Python

Lecture 3 Variables

Lecture 4 Type Conversion Examples

Lecture 5 Operators

Lecture 6 Operators Examples

Lecture 7 Collections

Lecture 8 List

Lecture 9 Multidimensional List Examples

Lecture 10 Tuples Examples

Lecture 11 Dictionaries Examples

Lecture 12 Ranges Examples

Lecture 13 Conditionials

Lecture 14 If Statements Examples

Lecture 15 If Statements Variants Examples

Lecture 16 Loops

Lecture 17 While Loops Examples

Lecture 18 For Loops Examples

Lecture 19 Functions

Lecture 20 Functions Examples

Lecture 21 Parameters and Return Values Examples

Lecture 22 Classes and Objects

Lecture 23 Classes Examples

Lecture 24 Objects Examples

Lecture 25 Inheritance Examples

Lecture 26 Static Members Examples

Lecture 27 Summary and Outro

Lecture 28 Intro to Python Slides

Lecture 29 Python_Language_Basics Code

Section 2: NumPy 2020

Lecture 30 Section Intro

Lecture 31 Intro to NumPy

Lecture 32 Installing NumPy

Lecture 33 Creating NumPy Arrays

Lecture 34 Creating NumPy Matrices

Lecture 35 Getting and Setting NumPy Elements

Lecture 36 Arithmetic Operations on NumPy Arrays

Lecture 37 NumPy Functions Part 1

Lecture 38 NumPy Functions Part 2

Lecture 39 Summary and Outro

Lecture 40 NumPy Slides

Lecture 41 NumPy code

Section 3: Pandas

Lecture 42 Section Intro

Lecture 43 Intro to Pandas

Lecture 44 Installing Pandas

Lecture 45 Creating Pandas Series

Lecture 46 Date Ranges

Lecture 47 Getting Elements from Series

Lecture 48 Getting Properties of Series

Lecture 49 Modifying Series

Lecture 50 Operations on Series

Lecture 51 Creating Pandas DataFrames

Lecture 52 Getting Elements from DataFrames

Lecture 53 Getting Properties from DataFrames

Lecture 54 DataFrame Modification

Lecture 55 DataFrame Operations

Lecture 56 DataFrame Comparisons and Iteration

Lecture 57 Reading CSV

Lecture 58 Summary and Outro

Lecture 59 Section Code

Lecture 60 Pandas Practice CSV

Lecture 61 Section Slides

Section 4: PyPlot

Lecture 62 Section Intro

Lecture 63 Intro to PyPlot

Lecture 64 Installing Matplotlib

Lecture 65 Basic Line Plot

Lecture 66 Customizing Graphs

Lecture 67 Plotting Multiple Datasets

Lecture 68 Bar Chart

Lecture 69 Pie Chart

Lecture 70 Histogram

Lecture 71 3D Plotting

Lecture 72 Course Outro

Lecture 73 Section Code

Section 5: Machine Learning Theory

Lecture 74 Section Intro

Lecture 75 Quick Intro to Machine Learning

Lecture 76 Deep Dive into Machine Learning

Lecture 77 Problems Solved with Machine Learning Part 1

Lecture 78 Problems Solved with Machine Learning Part 2

Lecture 79 Types of Machine Learning

Lecture 80 How Machine Learning Works

Lecture 81 Common Machine Learning Structures

Lecture 82 Steps to Build a Machine Learning Program

Lecture 83 Summary and Outro

Lecture 84 Intro to Machine Learning Slides

Section 6: Introduction to Tensorflow

Lecture 85 Section intro

Lecture 86 Intro to Tensorflow

Lecture 87 Installing Tenforflow

Lecture 88 Intro to Linear Regression

Lecture 89 Linear Regression Model - Creating Dataset

Lecture 90 Linear Regression Model - Building the Model

Lecture 91 Linear Regression Model - Creating a Loss Function

Lecture 92 Linear Regression Model - Training the Model

Lecture 93 Linear Regression Model - Testing the Model

Lecture 94 Summary and Outro

Lecture 95 Course Slides

Lecture 96 Course Code

Absolute beginners to programming,Developers transferring from other languages,Developers who need to learn machine learning