PirateBay Download | udemy preprocessing data numpy

udemy preprocessing data numpy

Type:: Other
Files:: 246
Size:: 2.5 GB
Uploaded On:: Jan. 12, 2021, 8:32 a.m.
Added By:: tuts756
Seeders:: 2
Leechers:: 1
Info Hash:: C33695DB39BCB46E17A50F6DCA1C636FA3B62996

Description The problem Most data analyst, data science, and coding courses miss a crucial practical step. They don’t teach you how to work with raw data, how to clean and preprocess it. This creates a sizeable gap between the skills you need on the job and the abilities you have acquired in training. Truth be told, real-world data is messy, so you need to know how to overcome this obstacle to become an independent data professional. The bootcamps we have seen online, and even live classes neglect this aspect and show you how to work with ‘clean’ data. But this isn’t doing you a favor. In reality, it will set you back both when you are applying for jobs, and when you’re on the job. The solution Our goal is to provide you with complete preparation using the NumPy package. This course will turn you into capable data analyst with a fantastic understanding of one of the most prominent computing packages in the world. To take you there, we will cover the following topics extensively. · The ndarray class and why we use it · The type of data arrays usually contain · Slicing and squeezing datasets · Dimensions of arrays, and how to reduce them · Generating pseudo-random data · Importing data from external text files · Saving/Exporting data to external files · Computing the statistics of the dataset (max, min, mean, variance, etc.) · Data cleaning · Data preprocessing · Final practical example Each of these subjects builds on the previous ones. And this is precisely what makes our curriculum so valuable. Everything is shown in the right order and we guarantee that you are not going to get lost along the way, as we have provided all necessary steps in video (not a single one skipped). In other words, we are not going to teach you how to concatenate datasets before you know how to index or slice them. So, to prepare you for the long journey towards a data science position, we created a course that will show you all the tools for the job: The Preprocessing Data with NumPy course [MG1] . We believe that this resource will significantly boost your chances of landing a job, as it will prepare you for practical tasks and concepts that are frequently included in interviews. NumPy is Python’s fundamental package for scientific computing. It has established itself as the go-to tool when you need to compute mathematical and statical operations. Why learn it? A large portion of a data analyst’s work is dedicated to preprocessing datasets. Unquestionably, this involves tons of mathematical and statistical techniques that NumPy is renowned for. What’s more, the package introduces multi-dimensional array structures and provides a plethora of built-in functions and methods to use while working with them. In other words, NumPy can be described as a computationally stable state-of-the-art Python instrument that provides great flexibility and can take your analysis to the next level. Some of the topics we will cover: 1. Fundamentals of NumPy 2. Random Generators 3. Working with text files 4. Statistics with NumPy 5. Data preprocessing 6. Final practical example 1. Fundamentals of NumPy To fully grasp the capabilities of NumPy, we need to start from the fundamentals. In this part of the course, we’ll examine the ndarray class, discuss why it’s so popular and get familiar with terms like “indexing”, “slicing”, “dimensions” and “reducing”. Why learn it? As stated above, NumPy is the quintessential package for scientific computing, and to understand its true value, we need to start from its very core – the ndarray class. The better we comprehend the basics, the easier it’s going to be to grasp the more difficult concepts. That’s why it’s fundamental to lay a good foundation on which to build our NumPy skills. 2. Random Generators After we’ve learned the basics, we’ll move on to pseudo-random data and random generators. These generators will help construct a set of arbitrary variables from a given probability distribution, or a fixed set of viable options. Why learn it? Working in a data-driven field, we sometimes need to construct partially arbitrary tests to see if our code works as intended. And here lies the value of random generators, as they allow us to construct datasets of pseudo-random data. The added benefit of random generators is that we can set a seed if we wish to replicate a particular randomization, but we’ll go into all the details in the course itself. 3. Working with text files Exchanging information with text files is practically how we exchange information today. In this part of the course, we will use the Python, pandas, and NumPy tools covered earlier to give you the essentials you need when importing or saving data. Why learn it? In many courses, you are just given a dataset to practice your analytical and programming skills. However, we don’t want to close our eyes to reality, where converting a raw dataset from an external file into a workable Python format can be a massive challenge. 4. Statistics with NumPy Once we’ve learned how to import large sets of information from external text files, we’ll finally be ready to explore one of NumPy’s strengths – statistics. Since the package is extremely computationally durable, we often rely on its functions and methods to calculate the statistics of a sample dataset. These include the likes of the mean, the standard deviation, and much more. Why learn it? To become a data scientist, you not only need to be able to preprocess a dataset, but also to extract valuable insights. One way to learn more about a dataset is by examining its statistics. So, we’ll use the package to understand more about the data and how to convert this knowledge into crucial information we can use for forecasting. 5. Data preprocessing Even when your dataset is in clean and comprehensible shape, it isn’t quite ready to be processed for visualizations and analysis just yet. There is a crucial step in between, and that’s data preprocessing. Why learn it? Data preprocessing is where a data analyst can demonstrate how good or great they are at their job. This stage of the work requires the ability to choose the right statistical tool that will improve the quality of your dataset and the knowledge to implement it with advanced pandas and NumPy techniques. Only when you’ve completed this step can you say that your dataset is preprocessed and ready for the next part, which is data visualization. 6. Practical example The course contains plenty of exercises and practical cases. What’s more, in the end, we have included a comprehensive practical example that will show you how everything you have learned along the way comes nicely together. This is where you will be able to appreciate how far you have come in your journey on mastering NumPy in your pursuit of a data career. What you get · Active Q&A support · All the NumPy knowledge to become a data analyst · A community of aspiring data analysts · A certificate of completion · Access to frequent future updates · Real-world training Get ready to become a NumPy data analyst from scratch Why wait? Every day is a missed opportunity. Click the “Buy Now” button and become a part of our data analyst program today. Who this course is for: Aspiring data analysts. Programming beginners. People interested in analyzing data through Python. Analysts who wish to specialize in Python. Finance graduates and professionals who need to better apply their knowledge in Python. Requirements You’ll need to install Python. No prior experience with NumPy is required. Some general understanding of coding languages is preferred, but not required. Last Updated 12/2020

Get This Torrent

[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/11. Stacking Arrays.mp4 74.5 MB
TutsNode.com.txt 63 bytes
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/3.1 FAQ-for-Udemy.pdf 243.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1.3 Preprocessing-Data-With-NumPy-Complete.ipynb 80.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/2. Download All Resources.html 694 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1.1 A-Loan-Data-Example-with-NumPy-Complete.ipynb 68.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/3.1 lending-co-LT.csv 58.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1.1 Lending-Company-Numeric-Data.csv 29.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1.5 A-Loan-Data-Example-with-NumPy-Template.ipynb 23.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/5. The NumPy Package and Its Applications.html 140 bytes
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/7. What is an array.srt 4.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/6. Installing and Upgrading NumPy.srt 2.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/6.1 Intro-to-NumPy-Template.ipynb 1.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/5.1 Lending-Company-Saving.csv 58.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1.2 Lending-company-Numeric.csv 29.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/1.1 Statistics-With-NumPy-Complete.ipynb 29.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1.3 Lending-Company-Numeric-Data-NAN.csv 28.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1.4 Lending-company-Numeric-NAN.csv 28.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/9. Introduction to NumPy - Exercise.html 833 bytes
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/10.1 Lending-Company-Total-Price.csv 22.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/1.2 Generating-Data-With-NumPy-Complete.ipynb 22.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/2. A Brief History of NumPy.html 140 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1.4 loan-data-dictionary.xlsx 19.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/3. FAQ.html 17.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/1.2 NumPy-Fundamentals-Complete.ipynb 17.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/7. Argument Functions - Part 1 Argument Where.srt 15.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1.1 Preprocessing-Data-With-NumPy-Template.ipynb 14.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1. Importing Data with Numpy - np.loadtxtx() vs np.genfromtxt().srt 14.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/5. Why Do We Use NumPy - Exercise.html 821 bytes
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/1. Basic Slicing.srt 13.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1.2 Importing-Text-Data-Complete.ipynb 13.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/11. Stacking Arrays.srt 13.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/5. Sorting Arrays.srt 13.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1. Checking for Missing Values.srt 12.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/1.1 Working-With-Arrays-Complete.ipynb 12.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/3. ndarrays.srt 12.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/2. Substituting Filler Values.srt 12.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/8. Manipulating Text Data Grade and Sub Grade.srt 11.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/1. Using NumPy Statistical Functions.srt 11.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/6. Histogram - Part 1 1-D Histograms.srt 11.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/3.2 Why-NumPy-Complete.ipynb 11.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/14. Manipulating Numeric Data Currency Change - From USD to EUR.srt 11.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/12. Manipulating Numeric Data Substitute Filler Values.srt 10.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/7. NumPy Fundamentals - Exercise.html 838 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/15. Completing the Dataset.srt 10.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/5. Saving Data with NumPy - NPY.srt 7.4 KB
.pad/0 71 bytes
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1. Importing Data with Numpy - np.loadtxtx() vs np.genfromtxt().mp4 72.7 MB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/5.2 Saving-Data-NP-Complete.ipynb 9.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/2. Importing Data with NumPy - Simple Cleaning when Importing.srt 9.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/8. Shuffling Data.srt 9.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/7. Manipulating Text Data Loan Status and Term.srt 9.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/3. Importing Data with NumPy - String vs Object vs Numbers.srt 9.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/3. Percentiles and Quantiles.srt 9.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/5. Working with Arrays - Exercise.html 841 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/13. Manipulating Numeric Data Currency Change – The Exchange Rate.srt 8.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/2. Minimal and Maximal Values.srt 8.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/4. Dimensions and the Squeeze Function.srt 8.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/4. Arrays vs Lists.srt 8.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/12. Concatenating Arrays.srt 8.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/4. NumPy Datatypes.srt 8.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/3. Reshaping Arrays.srt 8.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/1. Indexing.srt 8.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/10. Manipulating Text Data State Address.srt 8.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/1. Empty Arrays, Arrays of Identical Values.srt 7.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/9. Casting Arrays.srt 7.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/4. Random Generators and Seeds.srt 7.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/6. Random Probability Distributions.srt 7.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/1. What Does the Course Cover.srt 7.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/1.2 Statistics-With-NumPy-Template.ipynb 7.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/6. Argument Functions - Part 1 Argument Sort.srt 7.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/8. Generating Data with NumPy - Exercise.html 862 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/6. Manipulating Text Data Issue Date.srt 7.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/3. A Sequence of Numbers - np.arange().srt 7.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/13. Finding Unique Values in Arrays.srt 7.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1. Setting Up Introduction to the Practical Example.srt 6.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/8. Using the NumPy Documentation.srt 6.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/1.4 Importing-Text-Data-Template.ipynb 2.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/2. Stepwise Slicing.srt 6.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/3. Conditional Slicing.srt 6.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/4. Setting Up Splitting the Dataset.srt 6.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/6. Saving Data with NumPy - NPZ.srt 6.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/1.1 NumPy-Fundamentals-Template.ipynb 6.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/4. Importing Data with NumPy - Exercise.html 847 bytes
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/9. Manipulating Text Data Verification Status & URL.srt 6.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/5. Characteristics of NumPy Functions - Part 1.srt 6.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/1.1 Generating-Data-With-NumPy-Template.ipynb 5.1 KB
.pad/1 19 bytes
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/7. Argument Functions - Part 1 Argument Where.mp4 66.3 MB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/4. Averages and Variance.srt 6.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/3. Elementwise Properties.srt 6.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/7. Histogram - Part 2 Higher Dimension Histograms.srt 6.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/10. Stripping Symbols from Arrays.srt 5.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/8. Importing and Saving Data - Exercise.html 837 bytes
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/5. Random Integers, Probabilities and Choices.srt 5.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/3. Setting Up Checking for Incomplete Data.srt 5.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/4. Removing Values.srt 5.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/2. Assigning Values.srt 5.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/4. The NumPy Package and Its Applications.srt 5.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/7. Applications of Random Generators.srt 5.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/2. Setting Up Importing the Data Set.srt 5.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/7. Saving Data with NumPy - CSV.srt 5.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/6. Characteristics of NumPy Functions - Part 2.srt 5.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/1. A Brief History of NumPy.srt 4.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/2. _like Functions.srt 4.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/11. Manipulating Text Data Converting Strings and Creating a Checkpoint.srt 4.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/3.1 Why-NumPy-Template.ipynb 4.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/5. Covariance and Correlation.srt 4.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/1.2 Working-With-Arrays-Template.ipynb 4.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/8. N-A-N Equivalent Functions.srt 4.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/5. Setting Up Creating Checkpoints.srt 3.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/6.2 Intro-to-NumPy-Complete.ipynb 3.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/9. Statistics with NumPy - Exercise.html 847 bytes
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/5.3 Saving-Data-NP-Template.ipynb 3.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1.3 EUR-USD.csv 964 bytes
[TGx]Downloaded from torrentgalaxy.to .txt 585 bytes
.pad/2 131.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/5. Sorting Arrays.mp4 59.5 MB
.pad/3 15.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/1. What Does the Course Cover.mp4 58.7 MB
.pad/4 356.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/2. Importing Data with NumPy - Simple Cleaning when Importing.mp4 57.5 MB
.pad/5 493.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/15. Completing the Dataset.mp4 54.6 MB
.pad/6 360.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/14. Manipulating Numeric Data Currency Change - From USD to EUR.mp4 52.6 MB
.pad/7 368.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/1. Basic Slicing.mp4 52.2 MB
.pad/8 290.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1. Setting Up Introduction to the Practical Example.mp4 52.2 MB
.pad/9 338.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/1. Checking for Missing Values.mp4 52.0 MB
.pad/10 13.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/8. Manipulating Text Data Grade and Sub Grade.mp4 51.4 MB
.pad/11 77.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/3. ndarrays.mp4 50.1 MB
.pad/12 446.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/10. Manipulating Text Data State Address.mp4 49.6 MB
.pad/13 433.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/12. Concatenating Arrays.mp4 47.8 MB
.pad/14 217.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/12. Manipulating Numeric Data Substitute Filler Values.mp4 46.3 MB
.pad/15 161.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/9. Casting Arrays.mp4 45.6 MB
.pad/16 405.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/3. Reshaping Arrays.mp4 45.1 MB
.pad/17 404.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/1. Using NumPy Statistical Functions.mp4 44.1 MB
.pad/18 439.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/3. Importing Data with NumPy - String vs Object vs Numbers.mp4 43.8 MB
.pad/19 253.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/6. Histogram - Part 1 1-D Histograms.mp4 43.7 MB
.pad/20 320.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/8. Shuffling Data.mp4 42.6 MB
.pad/21 419.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/2. Substituting Filler Values.mp4 42.6 MB
.pad/22 427.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/7. Manipulating Text Data Loan Status and Term.mp4 40.4 MB
.pad/23 129.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/6. Argument Functions - Part 1 Argument Sort.mp4 38.4 MB
.pad/24 141.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/2. Setting Up Importing the Data Set.mp4 37.5 MB
.pad/25 468.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/8. Using the NumPy Documentation.mp4 37.3 MB
.pad/26 246.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/4. NumPy Datatypes.mp4 37.2 MB
.pad/27 337.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/4. The NumPy Package and Its Applications.mp4 37.0 MB
.pad/28 26.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/10. Stripping Symbols from Arrays.mp4 36.6 MB
.pad/29 394.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/6. Random Probability Distributions.mp4 36.3 MB
.pad/30 207.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/2. Minimal and Maximal Values.mp4 36.1 MB
.pad/31 437.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/13. Manipulating Numeric Data Currency Change – The Exchange Rate.mp4 35.8 MB
.pad/32 250.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/3. Percentiles and Quantiles.mp4 35.5 MB
.pad/33 476.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/13. Finding Unique Values in Arrays.mp4 35.5 MB
.pad/34 446 bytes
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/4. Random Generators and Seeds.mp4 35.4 MB
.pad/35 127.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/5. Saving Data with NumPy - NPY.mp4 34.8 MB
.pad/36 158.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/1. A Brief History of NumPy.mp4 34.7 MB
.pad/37 338.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/7. Applications of Random Generators.mp4 33.8 MB
.pad/38 214.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/4. Dimensions and the Squeeze Function.mp4 33.8 MB
.pad/39 230.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/4. Setting Up Splitting the Dataset.mp4 33.5 MB
.pad/40 506.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/5. Characteristics of NumPy Functions - Part 1.mp4 32.9 MB
.pad/41 66.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/9. Manipulating Text Data Verification Status & URL.mp4 32.7 MB
.pad/42 321.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/1. Indexing.mp4 30.5 MB
.pad/43 484.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/3. Setting Up Checking for Incomplete Data.mp4 30.3 MB
.pad/44 231.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/2. Why Do We Use NumPy/4. Arrays vs Lists.mp4 29.7 MB
.pad/45 307.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/6. Saving Data with NumPy - NPZ.mp4 29.6 MB
.pad/46 381.3 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/2. Stepwise Slicing.mp4 28.3 MB
.pad/47 168.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/6. Importing and Saving Data/7. Saving Data with NumPy - CSV.mp4 27.8 MB
.pad/48 239.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/4. Working with Arrays/3. Conditional Slicing.mp4 27.7 MB
.pad/49 264.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/1. Empty Arrays, Arrays of Identical Values.mp4 27.5 MB
.pad/50 14.7 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/6. Manipulating Text Data Issue Date.mp4 26.4 MB
.pad/51 148.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/3. Elementwise Properties.mp4 26.0 MB
.pad/52 486.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/5. Random Integers, Probabilities and Choices.mp4 26.0 MB
.pad/53 23.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/3. A Sequence of Numbers - np.arange().mp4 25.6 MB
.pad/54 399.4 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/4. Averages and Variance.mp4 25.3 MB
.pad/55 173.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/8. Manipulation Data with NumPy/4. Removing Values.mp4 25.3 MB
.pad/56 216.0 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/7. Histogram - Part 2 Higher Dimension Histograms.mp4 24.2 MB
.pad/57 296.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/6. Characteristics of NumPy Functions - Part 2.mp4 21.4 MB
.pad/58 94.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/11. Manipulating Text Data Converting Strings and Creating a Checkpoint.mp4 20.4 MB
.pad/59 94.9 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/5. Covariance and Correlation.mp4 20.3 MB
.pad/60 178.2 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/5. Setting Up Creating Checkpoints.mp4 20.0 MB
.pad/61 472.5 KB
[TutsNode.com] - Preprocessing Data with NumPy/3. NumPy Fundamentals/2. Assigning Values.mp4 19.7 MB
.pad/62 263.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/7. Statistics with NumPy/8. N-A-N Equivalent Functions.mp4 19.4 MB
.pad/63 91.6 KB
[TutsNode.com] - Preprocessing Data with NumPy/5. Generating Data with NumPy/2. _like Functions.mp4 17.4 MB
.pad/64 80.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/7. What is an array.mp4 15.6 MB
.pad/65 366.8 KB
[TutsNode.com] - Preprocessing Data with NumPy/1. Introduction to NumPy/6. Installing and Upgrading NumPy.mp4 8.4 MB
.pad/66 126.1 KB
[TutsNode.com] - Preprocessing Data with NumPy/9. A NumPy Practical Example/1.2 loan-data.csv 1.5 MB

Details for: Udemy - Preprocessing Data with NumPy

udemy preprocessing data numpy