Pickl AI

MAY 30, 2024

Understanding Data Science Data Science involves analysing and interpreting complex data sets to uncover valuable insights that can inform decision-making and solve real-world problems. You will collect and clean data from multiple sources, ensuring it is suitable for analysis.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

APRIL 10, 2023

With the growing proliferation and impact of data-driven decisions on different industries, having expertise in the Data Science domain will always have a positive impact. Student Go for Data Science Course? Yes, BSE students can opt for Data Science courses.

Data Science 52

Data Science Machine Learning Machine Learning Python 52

Pickl AI

JANUARY 12, 2023

Course Overview Statistics Data Science Python Apache Spark & Scala Tensorflow Tableau Course Eligibility To enroll for this Data Science course for working professionals, one needs to have a strong foundation in computer science, mathematics.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

IBM Journey to AI blog

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks.

Machine Learning 74

Machine Learning Machine Learning Supervised Learning Clustering 74

PyImageSearch

JANUARY 23, 2023

Applying XGBoost to Our Dataset Next, we will do some exploratory data analysis and prepare the data for feeding the model. unique() # check the label distribution lblDist = sns.countplot(x='quality', data=wineDf) On Lines 33 and 34 , we read the csv file and then display the unique labels we are dealing with.

Deep Learning 106

Deep Learning Deep Learning Algorithm Decision Trees 106

PyImageSearch

DECEMBER 12, 2022

. # load the data in the form of a csv estData = pd.read_csv("/content/realtor-data.csv") # drop NaN values from the dataset estData = estData.dropna() # split the labels and remove non-numeric data y = estData["price"].values Or requires a degree in computer science? values X = estData.drop(["price"], axis=1).select_dtypes(exclude=['object'])

Decision Trees 52

Decision Trees Deep Learning Deep Learning Exploratory Data Analysis 52

DrivenData Labs

DECEMBER 7, 2023

jimking100 ¶ Bonus prize : Best visualization Prize earned : $2,500 Team members : Jim King Usernames : jimking100 Hometown : Mill Valley, CA Background : I’m a successful real estate agent who happens to like data science. My Computer Science degree, MBA in Finance and 20 years in the tech field also help.

Natural Language Processing 130

Natural Language Processing Clustering Data Science Data Analysis 130

AWS Machine Learning Blog

SEPTEMBER 12, 2023

Email classification project diagram The workflow consists of the following components: Model experimentation – Data scientists use Amazon SageMaker Studio to carry out the first steps in the data science lifecycle: exploratory data analysis (EDA), data cleaning and preparation, and building prototype models.

Data Science 103

Data Science Data Scientist AWS ML 103