Machine Learning
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning analitikasi
Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 072 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 398-o'rinni va Suriya mintaqasida 232-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 40 072 obunachiga ega bo‘ldi.
23 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 379 ga, so‘nggi 24 soatda esa 30 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
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- Jalb etish (ER): Auditoriya o‘rtacha 1.92% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 1.16% ini tashkil etuvchi reaksiyalarni to‘playdi.
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Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 24 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
Method | What it does ----------------+-------------------- pd.read_csv() | Reads CSV file pd.read_excel() | Reads Excel file pd.read_sql() | Reads data from SQL pd.read_json() | Reads JSON file2. DATA ANALYSIS
Method | What it does --------------+--------------------------- df.head() | Shows first rows df.info() | Table information df.describe() | Statistics by columns df.shape | Table size (rows, columns) df.columns | List of column names3. DATA SELECTION
Method | What it does -----------+---------------------------------- df.loc[] | Selection by row and column names df.iloc[] | Selection by indices df.query() | Filtering by condition4. DATA CLEANING
Method | What it does ---------------------+-------------------------------- df.isnull() | Check for missing values (NULL) df.dropna() | Remove rows with missing values df.fillna() | Fill missing values df.drop_duplicates() | Remove duplicates df.astype() | Change data type5. ANALYTICS
Method | What it does ------------------+---------------------------- df.groupby() | Data grouping df.agg() | Aggregation in groups df.value_counts() | Count of unique values df.mean() | Mean value df.median() | Median df.corr() | Correlation between columns6. DATA MERGING
Method | What it does ------------+--------------------- pd.merge() | SQL JOIN by column pd.join() | JOIN by index pd.concat() | Glue tables together⭐ TOP 10 METHODS read_csv() head() info() loc[] iloc[] query() groupby() merge() fillna() sort_values()
Method | What it does
----------------+--------------------
pd.read_csv() | Reads CSV file
pd.read_excel() | Reads Excel file
pd.read_sql() | Reads data from SQL
pd.read_json() | Reads JSON file
2. DATA ANALYSIS
Method | What it does
--------------+---------------------------
df.head() | Shows first rows
df.info() | Table information
df.describe() | Statistics by columns
df.shape | Table size (rows, columns)
df.columns | List of column names
3. DATA SELECTION
Method | What it does
-----------+----------------------------------
df.loc[] | Selection by row and column names
df.iloc[] | Selection by indices
df.query() | Filtering by condition
4. DATA CLEANING
Method | What it does
---------------------+--------------------------------
df.isnull() | Check for missing values (NULL)
df.dropna() | Remove rows with missing values
df.fillna() | Fill missing values
df.drop_duplicates() | Remove duplicates
df.astype() | Change data type
5. ANALYTICS
Method | What it does
------------------+----------------------------
df.groupby() | Data grouping
df.agg() | Aggregation in groups
df.value_counts() | Count of unique values
df.mean() | Mean value
df.median() | Median
df.corr() | Correlation between columns
6. DATA MERGING
Method | What it does
------------+---------------------
pd.merge() | SQL JOIN by column
pd.join() | JOIN by index
pd.concat() | Glue tables together
⭐ TOP 10 METHODS
read_csv() head() info() loc[] iloc[] query() groupby() merge() fillna() sort_values()s = pd.Series([10, 15, 20, 25, 30])
s.loc[s > 20].loc[s % 2 == 1]
The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. 🤯
It's more reliable to gather everything into one expression:
s = pd.Series([10, 15, 20, 25, 30])
mask = (s > 20) & (s % 2 == 1)
result = s.loc[mask]
One mask, one point of truth. ✅
It's easier to debug. Fewer surprises when the code grows. 🚀
#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
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